# Splitifi Intelligence MCP (npm · splitifi-mcp)

Outcome predictions and judge profiles from 2,741 ML models trained on 30.3M court records.

- Trust score: 60/100 (medium)
- Change this week: +14
- Registry status: active
- Liveness: live
- Owner verified: no
- Last scored: 2026-08-03

## Components

- npm · `splitifi-mcp`: 60/100 (this document), [markdown](https://verifymcp.io/servers/mysplitifi-splitifi-mcp/splitifi-mcp.md), [page](https://verifymcp.io/servers/mysplitifi-splitifi-mcp/splitifi-mcp)

## Channel facts

- Registry: `npm`
- Package: `splitifi-mcp`
- Version: `2.1.1`
- Transport: `stdio`

## Trust breakdown

How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. Scores are 0–100 per category. Scoring method: https://verifymcp.io/docs/scoring (what has changed: https://verifymcp.io/docs/scoring/changelog)

Scored 2026-08-03.

- **Supply Chain Security**: 87/100
  - No malware found by supply-chain analysis.
  - Only part of the dependency tree could be resolved (95 of 99), so this covers what we could see, not the whole tree.
  - No install/post-install scripts declared.
  - Only part of the dependency tree could be resolved (95 of 99), so this covers what we could see, not the whole tree.
- **Provenance & Transparency**: 19/100
  - Repository check failed: the declared repository URL returned HTTP 404.
  - Provenance check failed: no build-provenance attestation is published.
  - Clear OSI-approved license (MIT).
  - Actively maintained (last published 11 days ago).
  - Security-disclosure policy not yet verified: we couldn't inspect the source repository.
- **Schema Quality & AI Usability**: 64/100
  - 100% of prompts and resources have a non-trivial description (not blank, and not just the item's name).
  - AI-judged instruction clarity (poor).
  - Tool/resource definitions use about 18569 tokens (~91/item across 202 items; 198 tools + 4 resources), lean.
  - Usage-examples check failed: none of the tools include examples.
- **Stability & Change Management**: 23/100
  - Stability observed for 7 of 30 days with no destabilising changes; credit accrues until the full window elapses.
- **Tool Coverage**: 93/100
  - 100% of tools have a non-trivial description (not blank, and not just the tool's name).
  - 79% of tool parameters carry a description.
- **Capabilities**: 100/100
  - Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.

## Install

### Claude

```bash
claude mcp add mysplitifi-splitifi-mcp -- npx -y splitifi-mcp
```

### Codex

```bash
codex mcp add mysplitifi-splitifi-mcp -- npx -y splitifi-mcp
```

### opencode

```json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "mysplitifi-splitifi-mcp": {
      "type": "local",
      "command": [
        "npx",
        "-y",
        "splitifi-mcp"
      ],
      "enabled": true
    }
  }
}
```

### OpenClaw

```bash
openclaw mcp add mysplitifi-splitifi-mcp --command npx --arg -y --arg splitifi-mcp
```

### Hermes

```yaml
mcp_servers:
  mysplitifi-splitifi-mcp:
    command: "npx"
    args: ["-y", "splitifi-mcp"]
```

### Other

```json
{
  "mcpServers": {
    "mysplitifi-splitifi-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "splitifi-mcp"
      ]
    }
  }
}
```

## Changelog

Every change recorded for this component, newest first. Days that predate change tracking, or that we cannot explain, say so: "we were watching and nothing happened" and "we were not watching" are different claims.

### 2026-08-02 (score 60, +40)

- [security regression] Provenance: unverified → fail
- [security improvement] Install scripts: unverified → pass
- [security improvement] Known CVEs: unverified → partial
- [security improvement] Malware scan: unverified → pass
- [functional regression] Tool coverage: 100 → unverified
- [functional regression] Schema quality: 100 → unverified
- [functional improvement] Dependency health: unverified → partial
- [functional improvement] Stability: unverified → 0.20
- [functional improvement] Maintenance: unverified → pass
- [functional improvement] MCP protocol: unverified → pass
- [functional improvement] Schema quality: unverified → poor
- [functional improvement] License: unverified → pass
- [functional] Licence: MIT

### 2026-07-31 (score 20, −26)

- [functional] We updated how we score, so this day's move reflects our rubric, not a change to the server

### 2026-07-27 (score 46)

First indexed and scored.

## MCP tools (198)

### `splitifi_start` (~185 tokens)

Start a guided Splitifi session. Declare your role (litigant, attorney, judge, mediator, paralegal, cdfa, forensic, gal, therapist), jurisdiction, and situation. Returns a personalized task plan and session_token to track progress. Optional — all tools work without it, but running this unlocks the full guided experience.

Input parameters:

- `jurisdiction` (string, required): State or province code, e.g. "FL", "TX", "ON"
- `role` (string, required): Your role: litigant, attorney, judge, mediator, paralegal, cdfa, forensic, gal, therapist
- `situation` (string): One sentence describing the situation
- `stage` (string): Where you are: pre-filing, filed, discovery, trial, post-decree
- `urgent_need` (string): Most urgent thing you need help with right now

### `splitifi_next_step` (~71 tokens)

Get the next recommended action in your case. Optionally mark a task as completed first. Returns next task, tool to call, and overall progress.

Input parameters:

- `completed_task_id` (string): ID of task just completed (optional)
- `session_token` (string, required): Your session token from splitifi_start

### `splitifi_my_tasks` (~52 tokens)

Get your full task list — what is done, pending, and what to do next. Requires a session token from splitifi_start.

Input parameters:

- `session_token` (string, required): Your session token from splitifi_start

### `splitifi_case_summary` (~51 tokens)

Get a full snapshot of your case: role, jurisdiction, situation, completed tasks, remaining steps, and what to do next.

Input parameters:

- `session_token` (string, required): Your session token from splitifi_start

### `splitifi_save_progress` (~101 tokens)

Save your session to a Splitifi account so you can pick up in any future conversation — with Claude, ChatGPT, or any AI. Creates an account if you do not have one. Returns a user_token to use instead of session_token going forward.

Input parameters:

- `email` (string, required): Your email address
- `password` (string, required): Password for your Splitifi account (min 8 chars)
- `session_token` (string, required): Your current session token

### `splitifi_login` (~50 tokens)

Resume a saved Splitifi session from a previous conversation. Pass your user_token from a previous splitifi_save_progress call.

Input parameters:

- `user_token` (string, required): Your saved user token from splitifi_save_progress

### `splitifi_predict_custody` (~132 tokens)

Predict custody outcome (sole vs joint, parenting time percentage) using ML models trained on 30.3M court records. Provide jurisdiction, optional judge_id, and case_facts describing the situation.

Input parameters:

- `case_facts` (object, required): Case details: marriage_length_years, num_children, income_disparity, domestic_violence, relocation, etc.
- `county` (string): County name for local court data
- `judge_id` (string): Judge ID for judge-specific prediction
- `jurisdiction` (string, required): State/province code, e.g. "TX", "ON"

### `splitifi_predict_asset_division` (~65 tokens)

Predict equitable distribution outcome by jurisdiction. Returns estimated split percentages and contested-item risk.

Input parameters:

- `case_facts` (object, required): total_assets, total_debts, marriage_length_years, income_disparity, separate_property_value
- `jurisdiction` (string, required)

### `splitifi_predict_spousal_support` (~72 tokens)

Predict spousal support (alimony) likelihood, duration, and amount range based on jurisdiction guidelines and case facts.

Input parameters:

- `case_facts` (object, required): marriage_length_years, income_higher, income_lower, standard_of_living, childcare_responsibilities
- `jurisdiction` (string, required)

### `splitifi_predict_child_support` (~61 tokens)

Predict child support obligation using jurisdiction-specific guidelines and ML models.

Input parameters:

- `case_facts` (object, required): income_payer, income_recipient, num_children, custody_arrangement, childcare_costs, health_insurance
- `jurisdiction` (string, required)

### `splitifi_predict_case_outcome` (~71 tokens)

General outcome prediction across multiple verticals: family_law, employment, immigration, criminal, or estate.

Input parameters:

- `case_facts` (object, required)
- `county` (string)
- `judge_id` (string)
- `jurisdiction` (string, required)
- `vertical` (string)

### `splitifi_predict_judge_empowerment` (~163 tokens)

Run a Pillars 11–20 judicial empowerment NLP model for a specific judge. These 160 LLM-powered models assess judicial decision style, empowerment patterns, ruling clarity, cognitive bias, and behavioral tendencies from 2.5M+ case records. Requires a jd_emp_p* model ID (e.g. jd_emp_p11_ruling_clarity).

Input parameters:

- `case_facts` (object): Case context for the empowerment assessment (case_type, jurisdiction, hearing_type, etc.)
- `judge_id` (string): Judge identifier string for personalized analysis
- `model_id` (string, required): NLP empowerment model ID — must start with jd_emp_p (Pillars 11–20). Example: jd_emp_p11_ruling_clarity

### `splitifi_find_judge` (~129 tokens)

Search for a judge by name, state, or county across 22,000+ indexed judges. Use this first when you have a judge's name but not their ID. Returns matching judges with court, case count, and judge_id for use with splitifi_judge_profile.

Input parameters:

- `county` (string): County name (e.g. "Palm Beach", "Cook")
- `name` (string): Judge name or partial name (e.g. "Shull", "Karen Miller")
- `state` (string): Two-letter state code (e.g. "FL", "CA")

### `splitifi_judge_profile` (~77 tokens)

Get behavioral profile for an indexed judge: grant rates, custody patterns, spousal support award rate, reversal rate. Pass the judge_id UUID from splitifi_find_judge, or pass a judge name directly for automatic lookup.

Input parameters:

- `judge_id` (string, required): Splitifi judge ID (UUID) or judge name for automatic lookup

### `splitifi_judge_comparable` (~56 tokens)

Get outcome distributions for cases similar to this one before a specific judge.

Input parameters:

- `case_type` (string)
- `filters` (object)
- `judge_id` (string, required)
- `jurisdiction` (string, required)

### `splitifi_jurisdiction_rules` (~76 tokens)

Get divorce rules for any US state, Canadian province, UK, or AU jurisdiction: waiting periods, residency requirements, fault vs no-fault, mediation requirements, filing fees.

Input parameters:

- `jurisdiction` (string, required): State/province code: "TX", "ON", "NSW", "EW" (England & Wales)

### `splitifi_custody_presumptions` (~53 tokens)

Get custody-specific rules: best interest factors, relocation standards, grandparent rights, parental alienation standards for a jurisdiction.

Input parameters:

- `case_type` (string)
- `jurisdiction` (string, required)

### `splitifi_asset_classifier` (~58 tokens)

Classify a list of assets as marital, separate, or mixed property with legal rationale. Handles commingled property, inheritance, gifts, and pre-marital assets.

Input parameters:

- `assets` (array, required)
- `jurisdiction` (string, required)

### `splitifi_settlement_analyzer` (~75 tokens)

Analyze a proposed settlement: estimate total value vs litigation outcome, flag below-market terms, and quantify savings vs going to trial.

Input parameters:

- `case_facts` (object)
- `jurisdiction` (string, required)
- `proposal` (object): Settlement terms: asset_split, support_amount, support_duration, custody_arrangement

### `splitifi_forensic_flags` (~61 tokens)

Detect financial red flags in divorce disclosures: income suppression, pre-filing asset transfers, missing business valuations, lifestyle vs reported income gaps.

Input parameters:

- `case_facts` (object)
- `disclosure_data` (object, required): Financial disclosure documents and reported values

### `splitifi_comparable_cases` (~72 tokens)

Get outcome distributions from 2.5M+ comparable cases: settlement percentages, median timelines, cost ranges, custody split distributions.

Input parameters:

- `case_type` (string)
- `filters` (object): Optional: marriage_length_range, asset_range, has_children, contested
- `jurisdiction` (string, required)

### `splitifi_pattern_mining` (~53 tokens)

Mine judicial behavior patterns, outcome trends, and disparity analysis by jurisdiction, case type, or judge.

Input parameters:

- `case_type` (string)
- `filters` (object)
- `jurisdiction` (string, required)

### `splitifi_strategy_paths` (~91 tokens)

Get ranked litigation strategy paths with timeline, cost, and risk for each: negotiation, mediation, collaborative law, or litigation. Uses 50-state decision trees.

Input parameters:

- `case_facts` (object)
- `case_type` (string)
- `current_state` (string): Where the case stands now: pre-filing, filed, discovery, trial-pending
- `jurisdiction` (string, required)

### `splitifi_calculate_child_support` (~172 tokens)

Calculate child support payment using jurisdiction-specific guidelines (Income Shares Model for most states). Returns monthly amount, annual amount, and formula explanation.

Input parameters:

- `childcare_cost` (number): Monthly childcare/daycare cost. Default: 0
- `custody_split_pct` (number): Percentage of time paying parent has custody (0-100). Default: 20
- `health_insurance_cost` (number): Monthly cost of children's health insurance. Default: 0
- `income_payer` (number, required): Monthly gross income of paying parent (USD)
- `income_recipient` (number, required): Monthly gross income of receiving parent (USD)
- `jurisdiction` (string, required): State code, e.g. "TX", "CA", "NY"
- `num_children` (number, required): Number of children subject to support

### `splitifi_calculate_divorce_cost` (~129 tokens)

Estimate total divorce cost including attorney fees, court fees, mediation, and expert costs. Returns low/high range and breakdown by phase.

Input parameters:

- `contested_level` (string): Default: Moderately Contested
- `country` (string): Country code: US, CA, GB, AU. Default: US
- `has_children` (boolean)
- `jurisdiction` (string, required): State/province code
- `plan_mediation` (boolean): Default: false
- `plan_to_hire_attorney` (boolean): Default: true
- `property_complexity` (string)

### `splitifi_calculate_property_division` (~137 tokens)

Estimate how marital property and debts will be divided. Handles community property states (50/50) and equitable distribution states. Returns each party's estimated share.

Input parameters:

- `assets` (object): { marital_home_value, retirement_accounts, bank_accounts, investments, vehicles_value, business_value, other_assets }
- `debts` (object): { home_mortgage_balance, credit_card_debt, other_debt }
- `jurisdiction` (string, required): State code: "CA", "TX", "NY", etc.
- `marriage_length_years` (number)
- `primary_earner` (string): Default: Equal

### `splitifi_calculate_home_buyout` (~136 tokens)

Calculate how much it costs to buy out a spouse's share of the marital home. Returns net equity, buyout amount, and estimated monthly payment after refinance.

Input parameters:

- `buyout_percentage` (number): Spouse's ownership percentage being bought out. Default: 50
- `home_value` (number, required): Current market value of the home (USD)
- `mortgage_balance` (number, required): Outstanding mortgage balance (USD)
- `refinance_costs` (number): Estimated refinance closing costs. Default: 0
- `selling_costs_percentage` (number): Estimated selling costs as % of value. Default: 8

### `splitifi_calculate_co_parenting` (~111 tokens)

Assess co-parenting compatibility and recommend a custody arrangement type (shared, parallel, primary with visitation, supervised).

Input parameters:

- `communication_quality` (string)
- `conflict_level` (string)
- `domestic_violence` (boolean): Whether domestic violence history exists
- `flexibility` (boolean): Whether both parents are flexible with scheduling
- `parenting_values_alignment` (string)
- `respect_level` (string)
- `substance_abuse` (boolean): Whether substance abuse concerns exist

### `splitifi_list_calculators` (~82 tokens)

List all available Splitifi calculators with IDs, categories, and descriptions. Use this to discover available calculators before calling splitifi_run_calculator.

Input parameters:

- `category` (string): Filter by category, e.g. "child_support", "property", "financial"
- `country` (string): Filter by country code: US, CA, GB, AU

### `splitifi_run_calculator` (~72 tokens)

Run any Splitifi calculator by its ID with provided inputs. Get available calculator IDs from splitifi_list_calculators first.

Input parameters:

- `calculator_id` (string, required): Calculator ID from splitifi_list_calculators, e.g. "child-support-us"
- `inputs` (object, required): Calculator-specific input fields

### `splitifi_list_forms` (~142 tokens)

List available divorce and family law forms for a jurisdiction (US state, Canadian province, UK, or AU). Returns form codes, names, filing fees, and categories.

Input parameters:

- `category` (string): Form category: petition, response, financial, custody, support, property, motion
- `country` (string): Country code: US, CA, GB, AU
- `page` (number): Page number for pagination. Default: 1
- `page_size` (number): Results per page. Default: 50, max: 100
- `state_province` (string): State or province code: TX, ON, NSW, etc.

### `splitifi_get_form` (~52 tokens)

Get a specific divorce form by ID with full field schema, instructions, filing fee, notarization requirements, and e-filing availability.

Input parameters:

- `form_id` (string, required): Form ID from splitifi_list_forms

### `splitifi_search_forms` (~86 tokens)

Search forms by keyword across a jurisdiction. Useful when you know the form name or number but not the ID.

Input parameters:

- `country` (string)
- `limit` (number): Max results. Default: 20
- `query` (string, required): Search term, e.g. "petition for dissolution" or "Form 8A"
- `state_province` (string)

### `splitifi_get_form_packet` (~127 tokens)

Get a recommended set of forms for a complete divorce or custody filing in a jurisdiction. Returns required forms, optional forms, total filing fee, and filing sequence.

Input parameters:

- `case_type` (string): divorce, custody, support, modification. Default: divorce
- `country` (string): Country code: US, CA, GB, AU. Default: US
- `state_province` (string): State/province code
- `user_situation` (object): { is_initiator: bool, has_children: bool, has_property: bool, needs_support: bool }

### `splitifi_form_categories` (~42 tokens)

Get available form categories for a jurisdiction. Useful before filtering splitifi_list_forms.

Input parameters:

- `country` (string)
- `state_province` (string)

### `splitifi_list_checklists` (~69 tokens)

List all available divorce checklists: pre-divorce preparation, financial documents, child custody, property division, court appearance, post-divorce, and safety planning.

Input parameters:

- `category` (string): Filter by category: preparation, documents, custody, property, court, post-divorce, safety

### `splitifi_get_checklist` (~93 tokens)

Get a full checklist with all items, priorities, and jurisdiction-specific notes. Use splitifi_list_checklists to discover available checklist IDs.

Input parameters:

- `checklist_id` (string, required): Checklist ID, e.g. "pre-divorce", "financial-docs", "child-custody", "property-division", "post-divorce"
- `jurisdiction` (string): Optional state/province code for jurisdiction-specific notes

### `splitifi_required_documents` (~117 tokens)

Get the specific documents a person needs to gather for their divorce based on their situation: whether they have children, a business, or real property.

Input parameters:

- `case_type` (string): divorce, custody, support. Default: divorce
- `has_business` (boolean): Whether either spouse owns a business. Default: false
- `has_children` (boolean): Default: false
- `has_property` (boolean): Whether marital real estate exists. Default: false
- `jurisdiction` (string): State/province code for jurisdiction-specific notes

### `splitifi_filing_steps` (~66 tokens)

Get the step-by-step filing procedure for a divorce or custody case in a specific jurisdiction.

Input parameters:

- `case_type` (string): divorce, custody, support. Default: divorce
- `jurisdiction` (string, required): State/province code, e.g. "TX", "ON"

### `splitifi_batch` (~87 tokens)

Run up to 50 Splitifi intelligence calls in a single request. Ideal for building case dashboards or running multiple analyses at once. Each request specifies a tool name and params.

Input parameters:

- `requests` (array, required): Array of { tool: string, params: object } — tool names match the REST API endpoint slugs (predict, judge-profile, comparable-cases, calculate-child-support, etc.)

### `splitifi_edgar_screen_defendant` (~83 tokens)

Screen a defendant company's financial health before filing. Returns Altman Z score, distress zone, win probability, dismissal risk, collectibility score, and duration forecast for the specified case type.

Input parameters:

- `case_type` (string, required): Litigation category (commercial, employment, insurance, healthcare, masstort)
- `company_name` (string, required): Defendant company name

### `splitifi_edgar_settlement_window` (~113 tokens)

Analyze optimal settlement timing based on defendant financial trajectory and case age. Returns a settlement pressure score (0-1), window status (opening/peak/closing/closed), and a recommended action.

Input parameters:

- `case_age_days` (number, required): Age of the case in days
- `case_id` (string): Optional case ID
- `case_type` (string, required): Litigation category
- `company_name` (string): Optional defendant company name
- `filing_date` (string): Optional ISO date of filing

### `splitifi_edgar_role_analysis` (~86 tokens)

Analyze the financial mismatch between plaintiff and defendant in a case. Returns plaintiff and defendant financial health, mismatch score, and role-separated outcome probabilities.

Input parameters:

- `case_id` (string): Optional case ID
- `case_type` (string): Optional litigation category
- `defendant_name` (string): Optional defendant company name
- `plaintiff_name` (string): Optional plaintiff company name

### `splitifi_edgar_monitoring` (~63 tokens)

Get EDGAR financial data refresh status. Returns last refresh timestamp, any defendants that crossed a financial distress zone boundary since the last refresh, and overall refresh health.

Input parameters:

- `case_ids` (array): Optional list of case IDs to filter; omit for all

### `splitifi_edgar_commercial_intel` (~111 tokens)

Bundle endpoint: run EDGAR defendant screen, settlement window analysis, and role analysis in parallel. Returns financial mismatch signal with settlement pressure and recommended action.

Input parameters:

- `case_age_days` (number): Case age in days (optional)
- `case_id` (string): Internal case ID (optional)
- `case_type` (string, required): Case vertical/type (required)
- `defendant_name` (string, required): Defendant company name (required)
- `plaintiff_name` (string): Plaintiff company name (optional)

### `splitifi_edgar_case_features` (~99 tokens)

Look up EDGAR-enriched financial features for a case by its FJC source ID. Returns Altman Z score, financial distress zone, leverage, liquidity, and outcome label from the 7,757-row FJC case features dataset. Useful for collection probability research and post-judgment recovery analysis.

Input parameters:

- `source_id` (string, required): FJC source ID for the case (e.g. "fjc:21944654")

### `splitifi_arbitration_screen` (~109 tokens)

Look up historical international arbitration outcomes by respondent country, sector, and case type. Returns claimant win rate, outcome distribution, average duration, and sample precedent cases from italaw/ICC/PCA/UNCITRAL database.

Input parameters:

- `ia_category` (string): Arbitration case type
- `respondent_country` (string): ISO 2-letter country code of the respondent state (e.g. "VE", "AR", "RU")
- `sector` (string): Industry sector of the dispute

### `splitifi_arbitration_stats` (~62 tokens)

Get aggregate international arbitration statistics: overall claimant win rates, breakdown by sector, respondent country, and case type. Based on ~6,000-8,000 cases from italaw, ICC, PCA, UNCITRAL, and EFTA Court.

### `splitifi_submit_outcome` (~99 tokens)

Submit the actual outcome of a case after a Splitifi prediction was made. This improves model accuracy over time. Optional but strongly encouraged.

Input parameters:

- `actual_outcome` (object, required): What actually happened: custody_type, support_amount, asset_split_pct, case_duration_days, etc.
- `case_id` (string): Optional case ID for your own reference
- `prediction_id` (string, required): The prediction ID returned by splitifi_predict_* tools

### `splitifi_timeline` (~86 tokens)

Estimate the timeline for your divorce case from now to final decree. Returns weeks remaining, key milestones, and what drives the timeline.

Input parameters:

- `contested_level` (string)
- `has_children` (boolean)
- `jurisdiction` (string, required): State/province code
- `stage` (string): Current stage: pre-filing, filed, discovery, trial, post-decree

### `splitifi_budget_planner` (~76 tokens)

Get a realistic budget for your divorce — total cost range, breakdown by category, and tips to reduce costs.

Input parameters:

- `contested_level` (string)
- `has_children` (boolean)
- `has_property` (boolean)
- `jurisdiction` (string, required)
- `plan_to_hire_attorney` (boolean)

### `splitifi_find_attorney` (~68 tokens)

Get guidance on finding a family law attorney in your jurisdiction, including what to look for and questions to ask.

Input parameters:

- `budget_range` (string): low, medium, high
- `case_type` (string): divorce, custody, support, modification
- `jurisdiction` (string, required)

### `splitifi_emotional_support` (~50 tokens)

Get emotional support resources, crisis hotlines, and guidance on what to expect emotionally during divorce.

Input parameters:

- `has_children` (boolean)
- `stage` (string): Current stage of your case

### `splitifi_parenting_plan` (~73 tokens)

Generate a parenting plan framework based on children's ages, parent schedules, and custody arrangement type.

Input parameters:

- `children_ages` (array): Ages of children
- `custody_type` (string)
- `jurisdiction` (string, required)
- `num_children` (number)
- `special_needs` (boolean)

### `splitifi_custody_schedule` (~84 tokens)

Get common custody schedule options (2-2-3, week-on-week-off, etc.) with pros/cons for each based on children's ages.

Input parameters:

- `jurisdiction` (string, required)
- `num_children` (number)
- `parent_work_schedules` (string): Describe each parent's work schedule
- `youngest_age` (number): Age of youngest child

### `splitifi_coparenting_guide` (~63 tokens)

Get a co-parenting guide: communication best practices, conflict reduction strategies, and child-centered approaches.

Input parameters:

- `children_ages` (array)
- `conflict_level` (string)
- `has_domestic_violence` (boolean)

### `splitifi_document_helper` (~74 tokens)

Get step-by-step help completing a specific court form. Explains each field, what to write, and common mistakes to avoid.

Input parameters:

- `form_id` (string, required): Form ID from splitifi_list_forms
- `jurisdiction` (string)
- `user_situation` (object): Your case details to pre-fill guidance

### `splitifi_support_modification` (~75 tokens)

Calculate whether you qualify for a child or spousal support modification and estimate the new amount.

Input parameters:

- `change_in_income` (number): Change in payer income (+ or -)
- `current_support` (number, required): Current monthly support amount
- `jurisdiction` (string, required)
- `reason` (string): Reason for modification request

### `splitifi_post_decree_checklist` (~68 tokens)

Get the post-divorce checklist: name change, beneficiary updates, asset retitling, insurance changes, estate planning.

Input parameters:

- `changed_name` (boolean)
- `has_children` (boolean)
- `has_property` (boolean)
- `jurisdiction` (string)

### `splitifi_safety_planning` (~61 tokens)

Get a safety planning checklist for situations involving domestic violence, coercive control, or concerns about the other party.

Input parameters:

- `has_children` (boolean)
- `jurisdiction` (string)
- `situation` (string): Brief description of safety concern

### `splitifi_court_appearance_prep` (~65 tokens)

Get a court appearance preparation guide: what to bring, what to wear, how to behave, and what to expect.

Input parameters:

- `hearing_type` (string): e.g. temporary orders, final hearing, contempt, modification
- `jurisdiction` (string)

### `splitifi_case_strategy` (~106 tokens)

Get a full case strategy for a family law matter: recommended path, immediate actions, and approach based on jurisdiction, stage, and assigned judge.

Input parameters:

- `case_facts` (object)
- `case_type` (string): divorce, custody, support, modification
- `judge_id` (string): Assigned judge ID (optional but improves strategy)
- `jurisdiction` (string, required)
- `stage` (string): pre-filing, filed, discovery, trial, post-decree

### `splitifi_motion_prep` (~70 tokens)

Get a motion preparation guide: key arguments, common mistakes, expected outcome, and filing checklist for any motion type.

Input parameters:

- `judge_id` (string)
- `jurisdiction` (string, required)
- `motion_type` (string, required): temporary_orders, summary_judgment, contempt, modification, enforcement

### `splitifi_discovery_checklist` (~69 tokens)

Get a complete discovery checklist for a family law matter: financial documents, interrogatories, depositions, and custody-specific discovery.

Input parameters:

- `case_type` (string)
- `has_business` (boolean)
- `has_retirement` (boolean)
- `jurisdiction` (string, required)

### `splitifi_deadline_tracker` (~70 tokens)

Get key case deadlines from filing date: service, answer, discovery cutoff, mediation, pretrial, trial.

Input parameters:

- `case_type` (string)
- `filing_date` (string): ISO date string, e.g. "2026-04-01"
- `jurisdiction` (string, required)

### `splitifi_billing_estimate` (~62 tokens)

Estimate total attorney fees for a matter based on jurisdiction rates, contested level, and complexity.

Input parameters:

- `case_type` (string)
- `contested_level` (string)
- `hours_estimated` (number)
- `jurisdiction` (string, required)

### `splitifi_opposing_counsel` (~69 tokens)

Analyze a settlement proposal from opposing counsel: is it fair vs comparable cases, what are the pressure points, and what to counter with.

Input parameters:

- `case_facts` (object)
- `jurisdiction` (string, required)
- `proposal` (object): Terms of opposing counsel's proposal

### `splitifi_deposition_prep` (~72 tokens)

Get deposition preparation questions for a witness based on their role and the case facts.

Input parameters:

- `case_type` (string)
- `key_issues` (array): Main issues to probe
- `witness_role` (string, required): e.g. client, spouse, accountant, business valuator, custody evaluator

### `splitifi_trial_readiness` (~62 tokens)

Score trial readiness and identify gaps: documents, witnesses, experts, discovery completion.

Input parameters:

- `case_facts` (object)
- `documents_ready` (boolean)
- `expert_retained` (boolean)
- `witnesses_identified` (boolean)

### `splitifi_client_intake` (~66 tokens)

Run a structured intake for a new family law client. Returns the key information to gather, questions to ask, and initial case assessment.

Input parameters:

- `case_type` (string)
- `client_situation` (string): Brief description from client
- `jurisdiction` (string, required)

### `splitifi_settlement_scenarios` (~68 tokens)

Model multiple settlement scenarios side by side: what each party gets, tax implications, and probability each would be accepted by a judge.

Input parameters:

- `case_facts` (object)
- `jurisdiction` (string, required)
- `scenarios` (array): Array of settlement proposals to compare

### `splitifi_case_brief` (~57 tokens)

Get a structured case brief with comparable ruling data. Suggests which Splitifi tools to run for deeper analysis.

Input parameters:

- `case_facts` (object)
- `case_type` (string)
- `jurisdiction` (string, required)

### `splitifi_ruling_patterns` (~62 tokens)

Get statewide ruling patterns for a case type: custody split distributions, support award medians, property division norms.

Input parameters:

- `case_type` (string)
- `judge_id` (string): Optional — returns judge-specific patterns
- `jurisdiction` (string, required)

### `splitifi_award_ranges` (~53 tokens)

Get award ranges for spousal support, attorney fees, or child support in a jurisdiction based on 2.5M+ cases.

Input parameters:

- `award_type` (string, required)
- `jurisdiction` (string, required)

### `splitifi_disparity_flags` (~50 tokens)

Identify jurisdictional outcome disparities — cases where outcomes diverge significantly from statewide norms.

Input parameters:

- `case_type` (string)
- `filters` (object)
- `jurisdiction` (string, required)

### `splitifi_mediation_agenda` (~83 tokens)

Build a structured mediation session agenda for the issues at hand. Returns timed agenda items and impasse guidance.

Input parameters:

- `issues` (array, required): Issues to mediate, e.g. ["property division", "custody", "support"]
- `jurisdiction` (string)
- `session_number` (number): Which session number this is. Default: 1

### `splitifi_impasse_strategy` (~69 tokens)

Get impasse-breaking strategies for a specific stuck issue: reframing, anchoring, caucus, single-text, and other techniques.

Input parameters:

- `conflict_level` (string)
- `impasse_issue` (string, required): The specific issue where parties are stuck
- `jurisdiction` (string)

### `splitifi_settlement_probability` (~66 tokens)

Estimate the probability of settlement vs trial for a case based on issue count, conflict level, and jurisdiction data.

Input parameters:

- `case_facts` (object)
- `conflict_level` (string)
- `contested_issues` (array)
- `jurisdiction` (string, required)

### `splitifi_disclosure_review` (~50 tokens)

Review financial disclosures for completeness and flag missing items. For CDFA and mediators reviewing financial statements.

Input parameters:

- `disclosure_data` (object, required): Financial disclosure documents provided
- `jurisdiction` (string)

### `splitifi_gal_framework` (~68 tokens)

Get a guardian ad litem assessment framework: factors to assess, interview approach by age, and report structure.

Input parameters:

- `allegations` (array): Any allegations of abuse, neglect, or DV
- `children_ages` (array): Ages of children
- `jurisdiction` (string, required)

### `splitifi_asset_tracing` (~76 tokens)

Get an asset tracing workflow for suspected hidden assets: steps, document requests, red flags to look for.

Input parameters:

- `jurisdiction` (string, required)
- `suspected_issues` (array): e.g. ["income suppression", "pre-filing transfers", "business undervaluation"]
- `total_estate_value` (number)

### `splitifi_document_queue` (~59 tokens)

Get a prioritized document preparation queue for a paralegal: which forms to prepare first, what information is needed, and filing sequence.

Input parameters:

- `case_type` (string)
- `jurisdiction` (string, required)
- `stage` (string)

### `splitifi_coparenting_therapy_guide` (~84 tokens)

Get a co-parenting therapy framework: session goals, interventions for high-conflict families, child-centered communication techniques.

Input parameters:

- `children_ages` (array)
- `conflict_level` (string)
- `has_domestic_violence` (boolean)
- `session_goal` (string): What you are trying to achieve this session

### `splitifi_funder_evaluate_case` (~267 tokens)

Score a litigation case for funding viability. Provide case facts (type, jurisdiction, judge, claimed damages, injury type, parties) and get back win probability, estimated award range, strategy paths with funder ROI, judge profile, comparable cases, and a funding recommendation (FUND/CONDITIONAL/PASS). Trained on 11.8M court outcomes across 1,184 ML models.

Input parameters:

- `case_type` (string, required): Type of case
- `claimed_damages` (number): Claimed damages in USD
- `county` (string): County name for local court data
- `expert_witness` (boolean): Is expert witness referenced?
- `external_ref` (string): Your internal case reference ID
- `funded_amount` (number): Intended funding amount for ROI calculation
- `injury_type` (string): Type of injury or harm alleged
- `judge_name` (string): Assigned judge full name if known
- `jurisdiction` (string, required): State abbreviation or province code, e.g. AZ, CA, ON
- `opposing_counsel` (string): Defense attorney or firm name
- `plaintiff_counsel` (string): Plaintiff attorney or firm name
- `prior_claims` (boolean): Has plaintiff made prior similar claims?

### `splitifi_funder_get_case` (~51 tokens)

Retrieve a previously evaluated case by ID, including all scoring, strategy paths, judge profile, and comparable cases.

Input parameters:

- `case_id` (string, required): Case ID returned from splitifi_evaluate_case

### `splitifi_funder_list_cases` (~50 tokens)

List all evaluated cases for your account with their recommendations and scores.

Input parameters:

- `limit` (number): Number of cases to return (max 100)
- `page` (number): Page number

### `splitifi_funder_judge_profile` (~85 tokens)

Get behavioral profile for a specific judge — plaintiff win rate, average award, settlement preference, trial rate, and pattern notes. Uses Splitifi's database of 16,302 verified judges.

Input parameters:

- `county` (string): County for local court data
- `judge_name` (string, required): Judge full name
- `jurisdiction` (string): State or province code

### `splitifi_funder_comparable_cases` (~105 tokens)

Find comparable case outcomes from 11.8M court records. Returns P25/P50/P75/P90 award distributions and anonymized comparable cases for a given case type and jurisdiction.

Input parameters:

- `case_type` (string, required)
- `claimed_damages` (number): Claimed amount for context
- `county` (string)
- `injury_type` (string): Type of injury for PI cases
- `jurisdiction` (string, required): State or province code

### `splitifi_funder_portfolio_health` (~82 tokens)

Get portfolio-level health analytics for your funded cases. Returns total funded exposure, average score, win probability distribution, exposure breakdown by case type and jurisdiction, and count of active monitoring alerts. Useful for IC presentations and investor reporting.

Input parameters:

- `portfolio_id` (string): Optional portfolio ID. If omitted, returns health across all funded cases for your account.

### `splitifi_funder_monitor_case` (~123 tokens)

Get the real-time monitoring timeline for a funded case. Returns all docket events detected by Splitifi's court harvester (CourtListener, Justia, 26 state portals), score deltas on each event, and a list of active alerts (JUDGE_REASSIGNMENT, KEY_MOTION_DENIED, TRIAL_TRACK_SET, etc.). Use this to track live developments on funded cases.

Input parameters:

- `case_id` (string, required): Case ID of the funded case to monitor (from splitifi_funder_evaluate_case or splitifi_funder_list_cases)

### `splitifi_predict_personal_injury` (~139 tokens)

Predict Personal Injury case outcome using ML models trained on 30.3M court records. Provide jurisdiction and case_facts (injury_type, liability_clarity, medical_costs, lost_wages, insurance_limit, fault_percentage).

Input parameters:

- `case_facts` (object, required): Case details for Personal Injury. Key fields: injury_type, liability_clarity, medical_costs, lost_wages, insurance_limit, fault_percentage
- `judge_id` (string): Optional — judge ID for judge-specific modifier
- `jurisdiction` (string, required): State/province/country code, e.g. "TX", "CA", "ON"

### `splitifi_comparable_personal_injury` (~108 tokens)

Comparable case outcomes from 2.5M+ Personal Injury cases matching your fact pattern. Returns outcome distribution, median resolution time, and jurisdiction trends.

Input parameters:

- `case_facts` (object, required): Case details for Personal Injury. Key fields: injury_type, liability_clarity, medical_costs, lost_wages, insurance_limit, fault_percentage
- `jurisdiction` (string, required): State/province code
- `limit` (number): Max cases to return (default 20)

### `splitifi_strategy_personal_injury` (~91 tokens)

Ranked strategy paths for Personal Injury cases — probability of success, estimated cost, and timeline for each path (negotiation, litigation, ADR).

Input parameters:

- `case_facts` (object, required): Case details for Personal Injury. Key fields: injury_type, liability_clarity, medical_costs, lost_wages, insurance_limit, fault_percentage
- `jurisdiction` (string, required): State/province code

### `splitifi_predict_criminal` (~126 tokens)

Predict Criminal Defense case outcome using ML models trained on 30.3M court records. Provide jurisdiction and case_facts (charge_type, charge_severity, prior_record, evidence_strength, plea_offer).

Input parameters:

- `case_facts` (object, required): Case details for Criminal Defense. Key fields: charge_type, charge_severity, prior_record, evidence_strength, plea_offer
- `judge_id` (string): Optional — judge ID for judge-specific modifier
- `jurisdiction` (string, required): State/province/country code, e.g. "TX", "CA", "ON"

### `splitifi_comparable_criminal` (~101 tokens)

Comparable case outcomes from 2.5M+ Criminal Defense cases matching your fact pattern. Returns outcome distribution, median resolution time, and jurisdiction trends.

Input parameters:

- `case_facts` (object, required): Case details for Criminal Defense. Key fields: charge_type, charge_severity, prior_record, evidence_strength, plea_offer
- `jurisdiction` (string, required): State/province code
- `limit` (number): Max cases to return (default 20)

### `splitifi_strategy_criminal` (~84 tokens)

Ranked strategy paths for Criminal Defense cases — probability of success, estimated cost, and timeline for each path (negotiation, litigation, ADR).

Input parameters:

- `case_facts` (object, required): Case details for Criminal Defense. Key fields: charge_type, charge_severity, prior_record, evidence_strength, plea_offer
- `jurisdiction` (string, required): State/province code

### `splitifi_predict_employment` (~126 tokens)

Predict Employment / Labor case outcome using ML models trained on 30.3M court records. Provide jurisdiction and case_facts (claim_type, employment_duration, termination_reason, documentation_quality, protected_class).

Input parameters:

- `case_facts` (object, required): Case details for Employment / Labor. Key fields: claim_type, employment_duration, termination_reason, documentation_quality, protected_class
- `judge_id` (string): Optional — judge ID for judge-specific modifier
- `jurisdiction` (string, required): State/province/country code, e.g. "TX", "CA", "ON"

### `splitifi_comparable_employment` (~102 tokens)

Comparable case outcomes from 2.5M+ Employment / Labor cases matching your fact pattern. Returns outcome distribution, median resolution time, and jurisdiction trends.

Input parameters:

- `case_facts` (object, required): Case details for Employment / Labor. Key fields: claim_type, employment_duration, termination_reason, documentation_quality, protected_class
- `jurisdiction` (string, required): State/province code
- `limit` (number): Max cases to return (default 20)

### `splitifi_strategy_employment` (~85 tokens)

Ranked strategy paths for Employment / Labor cases — probability of success, estimated cost, and timeline for each path (negotiation, litigation, ADR).

Input parameters:

- `case_facts` (object, required): Case details for Employment / Labor. Key fields: claim_type, employment_duration, termination_reason, documentation_quality, protected_class
- `jurisdiction` (string, required): State/province code

### `splitifi_predict_immigration` (~129 tokens)

Predict Immigration case outcome using ML models trained on 30.3M court records. Provide jurisdiction and case_facts (visa_type, country_of_origin, time_in_us, criminal_history, prior_applications).

Input parameters:

- `case_facts` (object, required): Case details for Immigration. Key fields: visa_type, country_of_origin, time_in_us, criminal_history, prior_applications
- `judge_id` (string): Optional — judge ID for judge-specific modifier
- `jurisdiction` (string, required): State/province/country code, e.g. "TX", "CA", "ON"

### `splitifi_comparable_immigration` (~102 tokens)

Comparable case outcomes from 2.5M+ Immigration cases matching your fact pattern. Returns outcome distribution, median resolution time, and jurisdiction trends.

Input parameters:

- `case_facts` (object, required): Case details for Immigration. Key fields: visa_type, country_of_origin, time_in_us, criminal_history, prior_applications
- `jurisdiction` (string, required): State/province code
- `limit` (number): Max cases to return (default 20)

### `splitifi_strategy_immigration` (~85 tokens)

Ranked strategy paths for Immigration cases — probability of success, estimated cost, and timeline for each path (negotiation, litigation, ADR).

Input parameters:

- `case_facts` (object, required): Case details for Immigration. Key fields: visa_type, country_of_origin, time_in_us, criminal_history, prior_applications
- `jurisdiction` (string, required): State/province code

### `splitifi_predict_civil_rights` (~126 tokens)

Predict Civil Rights case outcome using ML models trained on 30.3M court records. Provide jurisdiction and case_facts (rights_violation_type, agency_involved, documentation, damages_claimed).

Input parameters:

- `case_facts` (object, required): Case details for Civil Rights. Key fields: rights_violation_type, agency_involved, documentation, damages_claimed
- `judge_id` (string): Optional — judge ID for judge-specific modifier
- `jurisdiction` (string, required): State/province/country code, e.g. "TX", "CA", "ON"

### `splitifi_comparable_civil_rights` (~102 tokens)

Comparable case outcomes from 2.5M+ Civil Rights cases matching your fact pattern. Returns outcome distribution, median resolution time, and jurisdiction trends.

Input parameters:

- `case_facts` (object, required): Case details for Civil Rights. Key fields: rights_violation_type, agency_involved, documentation, damages_claimed
- `jurisdiction` (string, required): State/province code
- `limit` (number): Max cases to return (default 20)

### `splitifi_strategy_civil_rights` (~85 tokens)

Ranked strategy paths for Civil Rights cases — probability of success, estimated cost, and timeline for each path (negotiation, litigation, ADR).

Input parameters:

- `case_facts` (object, required): Case details for Civil Rights. Key fields: rights_violation_type, agency_involved, documentation, damages_claimed
- `jurisdiction` (string, required): State/province code

### `splitifi_predict_adr` (~139 tokens)

Predict ADR / Mediation case outcome using ML models trained on 30.3M court records. Provide jurisdiction and case_facts (dispute_type, parties_count, amount_in_controversy, prior_negotiation_attempts).

Input parameters:

- `case_facts` (object, required): Case details for ADR / Mediation. Key fields: dispute_type, parties_count, amount_in_controversy, prior_negotiation_attempts
- `judge_id` (string): Optional — judge ID for judge-specific modifier
- `jurisdiction` (string, required): State/province/country code, e.g. "TX", "CA", "ON"

### `splitifi_comparable_adr` (~109 tokens)

Comparable case outcomes from 2.5M+ ADR / Mediation cases matching your fact pattern. Returns outcome distribution, median resolution time, and jurisdiction trends.

Input parameters:

- `case_facts` (object, required): Case details for ADR / Mediation. Key fields: dispute_type, parties_count, amount_in_controversy, prior_negotiation_attempts
- `jurisdiction` (string, required): State/province code
- `limit` (number): Max cases to return (default 20)

### `splitifi_strategy_adr` (~92 tokens)

Ranked strategy paths for ADR / Mediation cases — probability of success, estimated cost, and timeline for each path (negotiation, litigation, ADR).

Input parameters:

- `case_facts` (object, required): Case details for ADR / Mediation. Key fields: dispute_type, parties_count, amount_in_controversy, prior_negotiation_attempts
- `jurisdiction` (string, required): State/province code

### `splitifi_predict_litigation` (~129 tokens)

Predict Litigation Analytics case outcome using ML models trained on 30.3M court records. Provide jurisdiction and case_facts (case_type, court_level, amount_in_controversy, discovery_complexity).

Input parameters:

- `case_facts` (object, required): Case details for Litigation Analytics. Key fields: case_type, court_level, amount_in_controversy, discovery_complexity
- `judge_id` (string): Optional — judge ID for judge-specific modifier
- `jurisdiction` (string, required): State/province/country code, e.g. "TX", "CA", "ON"

### `splitifi_comparable_litigation` (~103 tokens)

Comparable case outcomes from 2.5M+ Litigation Analytics cases matching your fact pattern. Returns outcome distribution, median resolution time, and jurisdiction trends.

Input parameters:

- `case_facts` (object, required): Case details for Litigation Analytics. Key fields: case_type, court_level, amount_in_controversy, discovery_complexity
- `jurisdiction` (string, required): State/province code
- `limit` (number): Max cases to return (default 20)

### `splitifi_strategy_litigation` (~86 tokens)

Ranked strategy paths for Litigation Analytics cases — probability of success, estimated cost, and timeline for each path (negotiation, litigation, ADR).

Input parameters:

- `case_facts` (object, required): Case details for Litigation Analytics. Key fields: case_type, court_level, amount_in_controversy, discovery_complexity
- `jurisdiction` (string, required): State/province code

### `splitifi_predict_game_theory` (~130 tokens)

Predict Game Theory / Strategy case outcome using ML models trained on 30.3M court records. Provide jurisdiction and case_facts (dispute_type, parties, payoff_structure, negotiation_rounds, reservation_values).

Input parameters:

- `case_facts` (object, required): Case details for Game Theory / Strategy. Key fields: dispute_type, parties, payoff_structure, negotiation_rounds, reservation_values
- `judge_id` (string): Optional — judge ID for judge-specific modifier
- `jurisdiction` (string, required): State/province/country code, e.g. "TX", "CA", "ON"

### `splitifi_comparable_game_theory` (~105 tokens)

Comparable case outcomes from 2.5M+ Game Theory / Strategy cases matching your fact pattern. Returns outcome distribution, median resolution time, and jurisdiction trends.

Input parameters:

- `case_facts` (object, required): Case details for Game Theory / Strategy. Key fields: dispute_type, parties, payoff_structure, negotiation_rounds, reservation_values
- `jurisdiction` (string, required): State/province code
- `limit` (number): Max cases to return (default 20)

### `splitifi_strategy_game_theory` (~88 tokens)

Ranked strategy paths for Game Theory / Strategy cases — probability of success, estimated cost, and timeline for each path (negotiation, litigation, ADR).

Input parameters:

- `case_facts` (object, required): Case details for Game Theory / Strategy. Key fields: dispute_type, parties, payoff_structure, negotiation_rounds, reservation_values
- `jurisdiction` (string, required): State/province code

### `splitifi_predict_appellate` (~129 tokens)

Predict Appellate case outcome using ML models trained on 30.3M court records. Provide jurisdiction and case_facts (trial_outcome, grounds_for_appeal, standard_of_review, circuit).

Input parameters:

- `case_facts` (object, required): Case details for Appellate. Key fields: trial_outcome, grounds_for_appeal, standard_of_review, circuit
- `judge_id` (string): Optional — judge ID for judge-specific modifier
- `jurisdiction` (string, required): State/province/country code, e.g. "TX", "CA", "ON"

### `splitifi_comparable_appellate` (~104 tokens)

Comparable case outcomes from 2.5M+ Appellate cases matching your fact pattern. Returns outcome distribution, median resolution time, and jurisdiction trends.

Input parameters:

- `case_facts` (object, required): Case details for Appellate. Key fields: trial_outcome, grounds_for_appeal, standard_of_review, circuit
- `jurisdiction` (string, required): State/province code
- `limit` (number): Max cases to return (default 20)

### `splitifi_strategy_appellate` (~87 tokens)

Ranked strategy paths for Appellate cases — probability of success, estimated cost, and timeline for each path (negotiation, litigation, ADR).

Input parameters:

- `case_facts` (object, required): Case details for Appellate. Key fields: trial_outcome, grounds_for_appeal, standard_of_review, circuit
- `jurisdiction` (string, required): State/province code

### `splitifi_predict_estate` (~122 tokens)

Predict Estate / Probate case outcome using ML models trained on 30.3M court records. Provide jurisdiction and case_facts (estate_value, will_present, beneficiaries_count, contested, state).

Input parameters:

- `case_facts` (object, required): Case details for Estate / Probate. Key fields: estate_value, will_present, beneficiaries_count, contested, state
- `judge_id` (string): Optional — judge ID for judge-specific modifier
- `jurisdiction` (string, required): State/province/country code, e.g. "TX", "CA", "ON"

### `splitifi_comparable_estate` (~100 tokens)

Comparable case outcomes from 2.5M+ Estate / Probate cases matching your fact pattern. Returns outcome distribution, median resolution time, and jurisdiction trends.

Input parameters:

- `case_facts` (object, required): Case details for Estate / Probate. Key fields: estate_value, will_present, beneficiaries_count, contested, state
- `jurisdiction` (string, required): State/province code
- `limit` (number): Max cases to return (default 20)

### `splitifi_strategy_estate` (~83 tokens)

Ranked strategy paths for Estate / Probate cases — probability of success, estimated cost, and timeline for each path (negotiation, litigation, ADR).

Input parameters:

- `case_facts` (object, required): Case details for Estate / Probate. Key fields: estate_value, will_present, beneficiaries_count, contested, state
- `jurisdiction` (string, required): State/province code

### `splitifi_predict_insurance` (~126 tokens)

Predict Insurance case outcome using ML models trained on 30.3M court records. Provide jurisdiction and case_facts (claim_type, policy_limit, coverage_dispute, bad_faith_indicators).

Input parameters:

- `case_facts` (object, required): Case details for Insurance. Key fields: claim_type, policy_limit, coverage_dispute, bad_faith_indicators
- `judge_id` (string): Optional — judge ID for judge-specific modifier
- `jurisdiction` (string, required): State/province/country code, e.g. "TX", "CA", "ON"

### `splitifi_comparable_insurance` (~100 tokens)

Comparable case outcomes from 2.5M+ Insurance cases matching your fact pattern. Returns outcome distribution, median resolution time, and jurisdiction trends.

Input parameters:

- `case_facts` (object, required): Case details for Insurance. Key fields: claim_type, policy_limit, coverage_dispute, bad_faith_indicators
- `jurisdiction` (string, required): State/province code
- `limit` (number): Max cases to return (default 20)

### `splitifi_strategy_insurance` (~83 tokens)

Ranked strategy paths for Insurance cases — probability of success, estimated cost, and timeline for each path (negotiation, litigation, ADR).

Input parameters:

- `case_facts` (object, required): Case details for Insurance. Key fields: claim_type, policy_limit, coverage_dispute, bad_faith_indicators
- `jurisdiction` (string, required): State/province code

### `splitifi_predict_legal_ethics` (~129 tokens)

Predict Legal Ethics case outcome using ML models trained on 30.3M court records. Provide jurisdiction and case_facts (violation_type, bar_jurisdiction, prior_discipline, harm_to_client).

Input parameters:

- `case_facts` (object, required): Case details for Legal Ethics. Key fields: violation_type, bar_jurisdiction, prior_discipline, harm_to_client
- `judge_id` (string): Optional — judge ID for judge-specific modifier
- `jurisdiction` (string, required): State/province/country code, e.g. "TX", "CA", "ON"

### `splitifi_comparable_legal_ethics` (~103 tokens)

Comparable case outcomes from 2.5M+ Legal Ethics cases matching your fact pattern. Returns outcome distribution, median resolution time, and jurisdiction trends.

Input parameters:

- `case_facts` (object, required): Case details for Legal Ethics. Key fields: violation_type, bar_jurisdiction, prior_discipline, harm_to_client
- `jurisdiction` (string, required): State/province code
- `limit` (number): Max cases to return (default 20)

### `splitifi_strategy_legal_ethics` (~86 tokens)

Ranked strategy paths for Legal Ethics cases — probability of success, estimated cost, and timeline for each path (negotiation, litigation, ADR).

Input parameters:

- `case_facts` (object, required): Case details for Legal Ethics. Key fields: violation_type, bar_jurisdiction, prior_discipline, harm_to_client
- `jurisdiction` (string, required): State/province code

### `splitifi_predict_class_action` (~118 tokens)

Predict Class Action case outcome using ML models trained on 30.3M court records. Provide jurisdiction and case_facts (claim_type, class_size, common_questions, defendant_resources).

Input parameters:

- `case_facts` (object, required): Case details for Class Action. Key fields: claim_type, class_size, common_questions, defendant_resources
- `judge_id` (string): Optional — judge ID for judge-specific modifier
- `jurisdiction` (string, required): State/province/country code, e.g. "TX", "CA", "ON"

### `splitifi_comparable_class_action` (~97 tokens)

Comparable case outcomes from 2.5M+ Class Action cases matching your fact pattern. Returns outcome distribution, median resolution time, and jurisdiction trends.

Input parameters:

- `case_facts` (object, required): Case details for Class Action. Key fields: claim_type, class_size, common_questions, defendant_resources
- `jurisdiction` (string, required): State/province code
- `limit` (number): Max cases to return (default 20)

### `splitifi_strategy_class_action` (~80 tokens)

Ranked strategy paths for Class Action cases — probability of success, estimated cost, and timeline for each path (negotiation, litigation, ADR).

Input parameters:

- `case_facts` (object, required): Case details for Class Action. Key fields: claim_type, class_size, common_questions, defendant_resources
- `jurisdiction` (string, required): State/province code

### `splitifi_predict_documents` (~119 tokens)

Predict Document Intelligence case outcome using ML models trained on 30.3M court records. Provide jurisdiction and case_facts (document_type, jurisdiction, complexity, parties_count, contested_terms).

Input parameters:

- `case_facts` (object, required): Case details for Document Intelligence. Key fields: document_type, jurisdiction, complexity, parties_count, contested_terms
- `judge_id` (string): Optional — judge ID for judge-specific modifier
- `jurisdiction` (string, required): State/province/country code, e.g. "TX", "CA", "ON"

### `splitifi_comparable_documents` (~97 tokens)

Comparable case outcomes from 2.5M+ Document Intelligence cases matching your fact pattern. Returns outcome distribution, median resolution time, and jurisdiction trends.

Input parameters:

- `case_facts` (object, required): Case details for Document Intelligence. Key fields: document_type, jurisdiction, complexity, parties_count, contested_terms
- `jurisdiction` (string, required): State/province code
- `limit` (number): Max cases to return (default 20)

### `splitifi_strategy_documents` (~80 tokens)

Ranked strategy paths for Document Intelligence cases — probability of success, estimated cost, and timeline for each path (negotiation, litigation, ADR).

Input parameters:

- `case_facts` (object, required): Case details for Document Intelligence. Key fields: document_type, jurisdiction, complexity, parties_count, contested_terms
- `jurisdiction` (string, required): State/province code

### `splitifi_predict_core` (~121 tokens)

Predict Core Prediction case outcome using ML models trained on 30.3M court records. Provide jurisdiction and case_facts (case_type, jurisdiction, complexity, procedural_stage, risk_factors).

Input parameters:

- `case_facts` (object, required): Case details for Core Prediction. Key fields: case_type, jurisdiction, complexity, procedural_stage, risk_factors
- `judge_id` (string): Optional — judge ID for judge-specific modifier
- `jurisdiction` (string, required): State/province/country code, e.g. "TX", "CA", "ON"

### `splitifi_comparable_core` (~98 tokens)

Comparable case outcomes from 2.5M+ Core Prediction cases matching your fact pattern. Returns outcome distribution, median resolution time, and jurisdiction trends.

Input parameters:

- `case_facts` (object, required): Case details for Core Prediction. Key fields: case_type, jurisdiction, complexity, procedural_stage, risk_factors
- `jurisdiction` (string, required): State/province code
- `limit` (number): Max cases to return (default 20)

### `splitifi_strategy_core` (~81 tokens)

Ranked strategy paths for Core Prediction cases — probability of success, estimated cost, and timeline for each path (negotiation, litigation, ADR).

Input parameters:

- `case_facts` (object, required): Case details for Core Prediction. Key fields: case_type, jurisdiction, complexity, procedural_stage, risk_factors
- `jurisdiction` (string, required): State/province code

### `splitifi_predict_family_law_deep` (~138 tokens)

Predict Family Law Deep / Forensic case outcome using ML models trained on 30.3M court records. Provide jurisdiction and case_facts (asset_types, income_sources, forensic_flags, hidden_asset_indicators). Requires premium add-on.

Input parameters:

- `case_facts` (object, required): Case details for Family Law Deep / Forensic. Key fields: asset_types, income_sources, forensic_flags, hidden_asset_indicators
- `judge_id` (string): Optional — judge ID for judge-specific modifier
- `jurisdiction` (string, required): State/province/country code, e.g. "TX", "CA", "ON"

### `splitifi_comparable_family_law_deep` (~110 tokens)

Comparable case outcomes from 2.5M+ Family Law Deep / Forensic cases matching your fact pattern. Returns outcome distribution, median resolution time, and jurisdiction trends.

Input parameters:

- `case_facts` (object, required): Case details for Family Law Deep / Forensic. Key fields: asset_types, income_sources, forensic_flags, hidden_asset_indicators
- `jurisdiction` (string, required): State/province code
- `limit` (number): Max cases to return (default 20)

### `splitifi_strategy_family_law_deep` (~93 tokens)

Ranked strategy paths for Family Law Deep / Forensic cases — probability of success, estimated cost, and timeline for each path (negotiation, litigation, ADR).

Input parameters:

- `case_facts` (object, required): Case details for Family Law Deep / Forensic. Key fields: asset_types, income_sources, forensic_flags, hidden_asset_indicators
- `jurisdiction` (string, required): State/province code

### `splitifi_predict_tax` (~130 tokens)

Predict Tax case outcome using ML models trained on 30.3M court records. Provide jurisdiction and case_facts (tax_type, years_involved, amount_owed, audit_trigger, compliance_history). Requires premium add-on.

Input parameters:

- `case_facts` (object, required): Case details for Tax. Key fields: tax_type, years_involved, amount_owed, audit_trigger, compliance_history
- `judge_id` (string): Optional — judge ID for judge-specific modifier
- `jurisdiction` (string, required): State/province/country code, e.g. "TX", "CA", "ON"

### `splitifi_comparable_tax` (~99 tokens)

Comparable case outcomes from 2.5M+ Tax cases matching your fact pattern. Returns outcome distribution, median resolution time, and jurisdiction trends.

Input parameters:

- `case_facts` (object, required): Case details for Tax. Key fields: tax_type, years_involved, amount_owed, audit_trigger, compliance_history
- `jurisdiction` (string, required): State/province code
- `limit` (number): Max cases to return (default 20)

### `splitifi_strategy_tax` (~82 tokens)

Ranked strategy paths for Tax cases — probability of success, estimated cost, and timeline for each path (negotiation, litigation, ADR).

Input parameters:

- `case_facts` (object, required): Case details for Tax. Key fields: tax_type, years_involved, amount_owed, audit_trigger, compliance_history
- `jurisdiction` (string, required): State/province code

### `splitifi_predict_real_estate` (~128 tokens)

Predict Real Estate case outcome using ML models trained on 30.3M court records. Provide jurisdiction and case_facts (transaction_type, property_value, contract_dispute, title_issues). Requires premium add-on.

Input parameters:

- `case_facts` (object, required): Case details for Real Estate. Key fields: transaction_type, property_value, contract_dispute, title_issues
- `judge_id` (string): Optional — judge ID for judge-specific modifier
- `jurisdiction` (string, required): State/province/country code, e.g. "TX", "CA", "ON"

### `splitifi_comparable_real_estate` (~100 tokens)

Comparable case outcomes from 2.5M+ Real Estate cases matching your fact pattern. Returns outcome distribution, median resolution time, and jurisdiction trends.

Input parameters:

- `case_facts` (object, required): Case details for Real Estate. Key fields: transaction_type, property_value, contract_dispute, title_issues
- `jurisdiction` (string, required): State/province code
- `limit` (number): Max cases to return (default 20)

### `splitifi_strategy_real_estate` (~83 tokens)

Ranked strategy paths for Real Estate cases — probability of success, estimated cost, and timeline for each path (negotiation, litigation, ADR).

Input parameters:

- `case_facts` (object, required): Case details for Real Estate. Key fields: transaction_type, property_value, contract_dispute, title_issues
- `jurisdiction` (string, required): State/province code

### `splitifi_predict_intellectual_property` (~132 tokens)

Predict IP / Patent case outcome using ML models trained on 30.3M court records. Provide jurisdiction and case_facts (ip_type, registration_status, infringement_type, prior_art, commercial_value). Requires premium add-on.

Input parameters:

- `case_facts` (object, required): Case details for IP / Patent. Key fields: ip_type, registration_status, infringement_type, prior_art, commercial_value
- `judge_id` (string): Optional — judge ID for judge-specific modifier
- `jurisdiction` (string, required): State/province/country code, e.g. "TX", "CA", "ON"

### `splitifi_comparable_intellectual_property` (~103 tokens)

Comparable case outcomes from 2.5M+ IP / Patent cases matching your fact pattern. Returns outcome distribution, median resolution time, and jurisdiction trends.

Input parameters:

- `case_facts` (object, required): Case details for IP / Patent. Key fields: ip_type, registration_status, infringement_type, prior_art, commercial_value
- `jurisdiction` (string, required): State/province code
- `limit` (number): Max cases to return (default 20)

### `splitifi_strategy_intellectual_property` (~86 tokens)

Ranked strategy paths for IP / Patent cases — probability of success, estimated cost, and timeline for each path (negotiation, litigation, ADR).

Input parameters:

- `case_facts` (object, required): Case details for IP / Patent. Key fields: ip_type, registration_status, infringement_type, prior_art, commercial_value
- `jurisdiction` (string, required): State/province code

### `splitifi_predict_securities` (~128 tokens)

Predict Securities / Finance case outcome using ML models trained on 30.3M court records. Provide jurisdiction and case_facts (violation_type, transaction_volume, materiality, disclosure_failures). Requires premium add-on.

Input parameters:

- `case_facts` (object, required): Case details for Securities / Finance. Key fields: violation_type, transaction_volume, materiality, disclosure_failures
- `judge_id` (string): Optional — judge ID for judge-specific modifier
- `jurisdiction` (string, required): State/province/country code, e.g. "TX", "CA", "ON"

### `splitifi_comparable_securities` (~100 tokens)

Comparable case outcomes from 2.5M+ Securities / Finance cases matching your fact pattern. Returns outcome distribution, median resolution time, and jurisdiction trends.

Input parameters:

- `case_facts` (object, required): Case details for Securities / Finance. Key fields: violation_type, transaction_volume, materiality, disclosure_failures
- `jurisdiction` (string, required): State/province code
- `limit` (number): Max cases to return (default 20)

### `splitifi_strategy_securities` (~83 tokens)

Ranked strategy paths for Securities / Finance cases — probability of success, estimated cost, and timeline for each path (negotiation, litigation, ADR).

Input parameters:

- `case_facts` (object, required): Case details for Securities / Finance. Key fields: violation_type, transaction_volume, materiality, disclosure_failures
- `jurisdiction` (string, required): State/province code

### `splitifi_predict_antitrust` (~129 tokens)

Predict Antitrust case outcome using ML models trained on 30.3M court records. Provide jurisdiction and case_facts (conduct_type, market_definition, market_share, harm_to_competition). Requires premium add-on.

Input parameters:

- `case_facts` (object, required): Case details for Antitrust. Key fields: conduct_type, market_definition, market_share, harm_to_competition
- `judge_id` (string): Optional — judge ID for judge-specific modifier
- `jurisdiction` (string, required): State/province/country code, e.g. "TX", "CA", "ON"

### `splitifi_comparable_antitrust` (~100 tokens)

Comparable case outcomes from 2.5M+ Antitrust cases matching your fact pattern. Returns outcome distribution, median resolution time, and jurisdiction trends.

Input parameters:

- `case_facts` (object, required): Case details for Antitrust. Key fields: conduct_type, market_definition, market_share, harm_to_competition
- `jurisdiction` (string, required): State/province code
- `limit` (number): Max cases to return (default 20)

### `splitifi_strategy_antitrust` (~83 tokens)

Ranked strategy paths for Antitrust cases — probability of success, estimated cost, and timeline for each path (negotiation, litigation, ADR).

Input parameters:

- `case_facts` (object, required): Case details for Antitrust. Key fields: conduct_type, market_definition, market_share, harm_to_competition
- `jurisdiction` (string, required): State/province code

### `splitifi_predict_bankruptcy` (~133 tokens)

Predict Bankruptcy case outcome using ML models trained on 30.3M court records. Provide jurisdiction and case_facts (chapter_type, total_debt, asset_value, income_means_test, creditor_count). Requires premium add-on.

Input parameters:

- `case_facts` (object, required): Case details for Bankruptcy. Key fields: chapter_type, total_debt, asset_value, income_means_test, creditor_count
- `judge_id` (string): Optional — judge ID for judge-specific modifier
- `jurisdiction` (string, required): State/province/country code, e.g. "TX", "CA", "ON"

### `splitifi_comparable_bankruptcy` (~101 tokens)

Comparable case outcomes from 2.5M+ Bankruptcy cases matching your fact pattern. Returns outcome distribution, median resolution time, and jurisdiction trends.

Input parameters:

- `case_facts` (object, required): Case details for Bankruptcy. Key fields: chapter_type, total_debt, asset_value, income_means_test, creditor_count
- `jurisdiction` (string, required): State/province code
- `limit` (number): Max cases to return (default 20)

### `splitifi_strategy_bankruptcy` (~84 tokens)

Ranked strategy paths for Bankruptcy cases — probability of success, estimated cost, and timeline for each path (negotiation, litigation, ADR).

Input parameters:

- `case_facts` (object, required): Case details for Bankruptcy. Key fields: chapter_type, total_debt, asset_value, income_means_test, creditor_count
- `jurisdiction` (string, required): State/province code

### `splitifi_predict_government_contracts` (~129 tokens)

Predict Government Contracts case outcome using ML models trained on 30.3M court records. Provide jurisdiction and case_facts (contract_value, agency, dispute_type, performance_issue, termination_type). Requires premium add-on.

Input parameters:

- `case_facts` (object, required): Case details for Government Contracts. Key fields: contract_value, agency, dispute_type, performance_issue, termination_type
- `judge_id` (string): Optional — judge ID for judge-specific modifier
- `jurisdiction` (string, required): State/province/country code, e.g. "TX", "CA", "ON"

### `splitifi_comparable_government_contracts` (~101 tokens)

Comparable case outcomes from 2.5M+ Government Contracts cases matching your fact pattern. Returns outcome distribution, median resolution time, and jurisdiction trends.

Input parameters:

- `case_facts` (object, required): Case details for Government Contracts. Key fields: contract_value, agency, dispute_type, performance_issue, termination_type
- `jurisdiction` (string, required): State/province code
- `limit` (number): Max cases to return (default 20)

### `splitifi_strategy_government_contracts` (~84 tokens)

Ranked strategy paths for Government Contracts cases — probability of success, estimated cost, and timeline for each path (negotiation, litigation, ADR).

Input parameters:

- `case_facts` (object, required): Case details for Government Contracts. Key fields: contract_value, agency, dispute_type, performance_issue, termination_type
- `jurisdiction` (string, required): State/province code

### `splitifi_predict_construction` (~128 tokens)

Predict Construction case outcome using ML models trained on 30.3M court records. Provide jurisdiction and case_facts (dispute_type, contract_value, delay_days, defect_type, bond_present). Requires premium add-on.

Input parameters:

- `case_facts` (object, required): Case details for Construction. Key fields: dispute_type, contract_value, delay_days, defect_type, bond_present
- `judge_id` (string): Optional — judge ID for judge-specific modifier
- `jurisdiction` (string, required): State/province/country code, e.g. "TX", "CA", "ON"

### `splitifi_comparable_construction` (~98 tokens)

Comparable case outcomes from 2.5M+ Construction cases matching your fact pattern. Returns outcome distribution, median resolution time, and jurisdiction trends.

Input parameters:

- `case_facts` (object, required): Case details for Construction. Key fields: dispute_type, contract_value, delay_days, defect_type, bond_present
- `jurisdiction` (string, required): State/province code
- `limit` (number): Max cases to return (default 20)

### `splitifi_strategy_construction` (~81 tokens)

Ranked strategy paths for Construction cases — probability of success, estimated cost, and timeline for each path (negotiation, litigation, ADR).

Input parameters:

- `case_facts` (object, required): Case details for Construction. Key fields: dispute_type, contract_value, delay_days, defect_type, bond_present
- `jurisdiction` (string, required): State/province code

### `splitifi_predict_healthcare` (~137 tokens)

Predict Healthcare / Malpractice case outcome using ML models trained on 30.3M court records. Provide jurisdiction and case_facts (claim_type, procedure, outcome, standard_of_care_deviation, damages_type). Requires premium add-on.

Input parameters:

- `case_facts` (object, required): Case details for Healthcare / Malpractice. Key fields: claim_type, procedure, outcome, standard_of_care_deviation, damages_type
- `judge_id` (string): Optional — judge ID for judge-specific modifier
- `jurisdiction` (string, required): State/province/country code, e.g. "TX", "CA", "ON"

### `splitifi_comparable_healthcare` (~106 tokens)

Comparable case outcomes from 2.5M+ Healthcare / Malpractice cases matching your fact pattern. Returns outcome distribution, median resolution time, and jurisdiction trends.

Input parameters:

- `case_facts` (object, required): Case details for Healthcare / Malpractice. Key fields: claim_type, procedure, outcome, standard_of_care_deviation, damages_type
- `jurisdiction` (string, required): State/province code
- `limit` (number): Max cases to return (default 20)

### `splitifi_strategy_healthcare` (~89 tokens)

Ranked strategy paths for Healthcare / Malpractice cases — probability of success, estimated cost, and timeline for each path (negotiation, litigation, ADR).

Input parameters:

- `case_facts` (object, required): Case details for Healthcare / Malpractice. Key fields: claim_type, procedure, outcome, standard_of_care_deviation, damages_type
- `jurisdiction` (string, required): State/province code

### `splitifi_predict_environmental` (~120 tokens)

Predict Environmental case outcome using ML models trained on 30.3M court records. Provide jurisdiction and case_facts (violation_type, contamination_level, remediation_cost, agency). Requires premium add-on.

Input parameters:

- `case_facts` (object, required): Case details for Environmental. Key fields: violation_type, contamination_level, remediation_cost, agency
- `judge_id` (string): Optional — judge ID for judge-specific modifier
- `jurisdiction` (string, required): State/province/country code, e.g. "TX", "CA", "ON"

### `splitifi_comparable_environmental` (~94 tokens)

Comparable case outcomes from 2.5M+ Environmental cases matching your fact pattern. Returns outcome distribution, median resolution time, and jurisdiction trends.

Input parameters:

- `case_facts` (object, required): Case details for Environmental. Key fields: violation_type, contamination_level, remediation_cost, agency
- `jurisdiction` (string, required): State/province code
- `limit` (number): Max cases to return (default 20)

### `splitifi_strategy_environmental` (~77 tokens)

Ranked strategy paths for Environmental cases — probability of success, estimated cost, and timeline for each path (negotiation, litigation, ADR).

Input parameters:

- `case_facts` (object, required): Case details for Environmental. Key fields: violation_type, contamination_level, remediation_cost, agency
- `jurisdiction` (string, required): State/province code

### `splitifi_predict_cybersecurity` (~125 tokens)

Predict Cybersecurity case outcome using ML models trained on 30.3M court records. Provide jurisdiction and case_facts (incident_type, data_volume, breach_scope, notification_status). Requires premium add-on.

Input parameters:

- `case_facts` (object, required): Case details for Cybersecurity. Key fields: incident_type, data_volume, breach_scope, notification_status
- `judge_id` (string): Optional — judge ID for judge-specific modifier
- `jurisdiction` (string, required): State/province/country code, e.g. "TX", "CA", "ON"

### `splitifi_comparable_cybersecurity` (~99 tokens)

Comparable case outcomes from 2.5M+ Cybersecurity cases matching your fact pattern. Returns outcome distribution, median resolution time, and jurisdiction trends.

Input parameters:

- `case_facts` (object, required): Case details for Cybersecurity. Key fields: incident_type, data_volume, breach_scope, notification_status
- `jurisdiction` (string, required): State/province code
- `limit` (number): Max cases to return (default 20)

### `splitifi_strategy_cybersecurity` (~82 tokens)

Ranked strategy paths for Cybersecurity cases — probability of success, estimated cost, and timeline for each path (negotiation, litigation, ADR).

Input parameters:

- `case_facts` (object, required): Case details for Cybersecurity. Key fields: incident_type, data_volume, breach_scope, notification_status
- `jurisdiction` (string, required): State/province code

### `splitifi_predict_emerging_technology` (~125 tokens)

Predict Emerging Technology case outcome using ML models trained on 30.3M court records. Provide jurisdiction and case_facts (tech_type, dispute_category, regulatory_body, harm_type). Requires premium add-on.

Input parameters:

- `case_facts` (object, required): Case details for Emerging Technology. Key fields: tech_type, dispute_category, regulatory_body, harm_type
- `judge_id` (string): Optional — judge ID for judge-specific modifier
- `jurisdiction` (string, required): State/province/country code, e.g. "TX", "CA", "ON"

### `splitifi_comparable_emerging_technology` (~99 tokens)

Comparable case outcomes from 2.5M+ Emerging Technology cases matching your fact pattern. Returns outcome distribution, median resolution time, and jurisdiction trends.

Input parameters:

- `case_facts` (object, required): Case details for Emerging Technology. Key fields: tech_type, dispute_category, regulatory_body, harm_type
- `jurisdiction` (string, required): State/province code
- `limit` (number): Max cases to return (default 20)

### `splitifi_strategy_emerging_technology` (~82 tokens)

Ranked strategy paths for Emerging Technology cases — probability of success, estimated cost, and timeline for each path (negotiation, litigation, ADR).

Input parameters:

- `case_facts` (object, required): Case details for Emerging Technology. Key fields: tech_type, dispute_category, regulatory_body, harm_type
- `jurisdiction` (string, required): State/province code

### `splitifi_predict_sports_entertainment` (~134 tokens)

Predict Sports / Entertainment case outcome using ML models trained on 30.3M court records. Provide jurisdiction and case_facts (contract_type, dispute_nature, contract_value, league_rules_applicable). Requires premium add-on.

Input parameters:

- `case_facts` (object, required): Case details for Sports / Entertainment. Key fields: contract_type, dispute_nature, contract_value, league_rules_applicable
- `judge_id` (string): Optional — judge ID for judge-specific modifier
- `jurisdiction` (string, required): State/province/country code, e.g. "TX", "CA", "ON"

### `splitifi_comparable_sports_entertainment` (~105 tokens)

Comparable case outcomes from 2.5M+ Sports / Entertainment cases matching your fact pattern. Returns outcome distribution, median resolution time, and jurisdiction trends.

Input parameters:

- `case_facts` (object, required): Case details for Sports / Entertainment. Key fields: contract_type, dispute_nature, contract_value, league_rules_applicable
- `jurisdiction` (string, required): State/province code
- `limit` (number): Max cases to return (default 20)

### `splitifi_strategy_sports_entertainment` (~88 tokens)

Ranked strategy paths for Sports / Entertainment cases — probability of success, estimated cost, and timeline for each path (negotiation, litigation, ADR).

Input parameters:

- `case_facts` (object, required): Case details for Sports / Entertainment. Key fields: contract_type, dispute_nature, contract_value, league_rules_applicable
- `jurisdiction` (string, required): State/province code

### `splitifi_predict_international_trade` (~130 tokens)

Predict International Trade case outcome using ML models trained on 30.3M court records. Provide jurisdiction and case_facts (trade_type, countries_involved, tariff_dispute, sanctions_exposure). Requires premium add-on.

Input parameters:

- `case_facts` (object, required): Case details for International Trade. Key fields: trade_type, countries_involved, tariff_dispute, sanctions_exposure
- `judge_id` (string): Optional — judge ID for judge-specific modifier
- `jurisdiction` (string, required): State/province/country code, e.g. "TX", "CA", "ON"

### `splitifi_comparable_international_trade` (~101 tokens)

Comparable case outcomes from 2.5M+ International Trade cases matching your fact pattern. Returns outcome distribution, median resolution time, and jurisdiction trends.

Input parameters:

- `case_facts` (object, required): Case details for International Trade. Key fields: trade_type, countries_involved, tariff_dispute, sanctions_exposure
- `jurisdiction` (string, required): State/province code
- `limit` (number): Max cases to return (default 20)

### `splitifi_strategy_international_trade` (~84 tokens)

Ranked strategy paths for International Trade cases — probability of success, estimated cost, and timeline for each path (negotiation, litigation, ADR).

Input parameters:

- `case_facts` (object, required): Case details for International Trade. Key fields: trade_type, countries_involved, tariff_dispute, sanctions_exposure
- `jurisdiction` (string, required): State/province code

### `splitifi_predict_judge_analytics` (~123 tokens)

Predict Judge Analytics case outcome using ML models trained on 30.3M court records. Provide jurisdiction and case_facts (judge_id, case_type, motion_type, jurisdiction). Requires premium add-on.

Input parameters:

- `case_facts` (object, required): Case details for Judge Analytics. Key fields: judge_id, case_type, motion_type, jurisdiction
- `judge_id` (string): Optional — judge ID for judge-specific modifier
- `jurisdiction` (string, required): State/province/country code, e.g. "TX", "CA", "ON"

### `splitifi_comparable_judge_analytics` (~98 tokens)

Comparable case outcomes from 2.5M+ Judge Analytics cases matching your fact pattern. Returns outcome distribution, median resolution time, and jurisdiction trends.

Input parameters:

- `case_facts` (object, required): Case details for Judge Analytics. Key fields: judge_id, case_type, motion_type, jurisdiction
- `jurisdiction` (string, required): State/province code
- `limit` (number): Max cases to return (default 20)

### `splitifi_strategy_judge_analytics` (~81 tokens)

Ranked strategy paths for Judge Analytics cases — probability of success, estimated cost, and timeline for each path (negotiation, litigation, ADR).

Input parameters:

- `case_facts` (object, required): Case details for Judge Analytics. Key fields: judge_id, case_type, motion_type, jurisdiction
- `jurisdiction` (string, required): State/province code

### `splitifi_predict_firm_analytics` (~123 tokens)

Predict Firm Analytics case outcome using ML models trained on 30.3M court records. Provide jurisdiction and case_facts (firm_id, practice_area, case_type, jurisdiction). Requires premium add-on.

Input parameters:

- `case_facts` (object, required): Case details for Firm Analytics. Key fields: firm_id, practice_area, case_type, jurisdiction
- `judge_id` (string): Optional — judge ID for judge-specific modifier
- `jurisdiction` (string, required): State/province/country code, e.g. "TX", "CA", "ON"

### `splitifi_comparable_firm_analytics` (~98 tokens)

Comparable case outcomes from 2.5M+ Firm Analytics cases matching your fact pattern. Returns outcome distribution, median resolution time, and jurisdiction trends.

Input parameters:

- `case_facts` (object, required): Case details for Firm Analytics. Key fields: firm_id, practice_area, case_type, jurisdiction
- `jurisdiction` (string, required): State/province code
- `limit` (number): Max cases to return (default 20)

### `splitifi_strategy_firm_analytics` (~81 tokens)

Ranked strategy paths for Firm Analytics cases — probability of success, estimated cost, and timeline for each path (negotiation, litigation, ADR).

Input parameters:

- `case_facts` (object, required): Case details for Firm Analytics. Key fields: firm_id, practice_area, case_type, jurisdiction
- `jurisdiction` (string, required): State/province code

### `splitifi_jurisdiction_intelligence` (~97 tokens)

Get jurisdiction-level intelligence features for a state and optionally a specific county. Returns wage baselines, economic indicators, court statistics, and composite risk scores keyed by geography.

Input parameters:

- `county_fips` (string): 5-digit county FIPS code (optional, e.g. 06037 for Los Angeles County)
- `state` (string, required): 2-letter US state code (e.g. CA, TX, FL)

### `splitifi_jurisdiction_wages` (~90 tokens)

Get BLS occupational wage data for a state and metro area. Returns median and 75th percentile hourly wages for use in personal injury damages calculations.

Input parameters:

- `msa_code` (string): BLS MSA area code (optional, e.g. 31080 for Los Angeles metro)
- `state` (string, required): 2-letter US state code (e.g. CA, TX)

### `splitifi_eu_corporate_screen` (~119 tokens)

Screen a company against 6 European corporate registries (Norway/Brreg, Switzerland/ZEFIX, Ireland/CRO, France/SIRENE, Netherlands/KVK, Poland/KRS). Returns matched registry IDs, employee counts, capital figures, dissolution flags, and cross-border presence score.

Input parameters:

- `company_name` (string, required): Full or partial company name to look up
- `country_hint` (string): Optional ISO-2 country code (NO, CH, IE, FR, NL, PL) to prioritize matching

### `splitifi_eu_corporate_stats` (~56 tokens)

Returns aggregate coverage statistics for the EU corporate registry dataset: total entities ingested, per-registry counts (Brreg/ZEFIX/CRO/SIRENE/KVK/KRS), and cross-border entity count.

### `splitifi_international_screen` (~104 tokens)

Screen a company for international financial distress. Auto-routes by jurisdiction (UK/CA/AU/other) using optional country_hint. Returns matched company data, distress zone, and jurisdiction-specific financial indicators from Companies House, SEDAR+, ASIC, and OpenCorporates.

Input parameters:

- `company_name` (string, required): Full legal company name
- `country_hint` (string): Optional ISO country code: gb (UK), ca (Canada), au (Australia), etc.

### `splitifi_international_uk_screen` (~61 tokens)

Screen a UK-registered company via Companies House data. Returns charges count, company status (active/dissolved/liquidation), Altman Z distress zone, and accounts filing date.

Input parameters:

- `company_name` (string, required): UK company name

### `splitifi_international_ca_screen` (~49 tokens)

Screen a Canadian company via SEDAR+ financial filings. Returns total assets, total liabilities, filing date, and distress zone.

Input parameters:

- `company_name` (string, required): Canadian company name

### `splitifi_international_au_screen` (~53 tokens)

Screen an Australian company via ASIC registration data. Returns company status (registered/deregistered/under_administration) and deregistration date if applicable.

Input parameters:

- `company_name` (string, required): Australian company name

### `ssa_alj_screen` (~81 tokens)

Look up an SSA Administrative Law Judge by name. Returns allowance rate, denial rate, dismissal rate, total decisions, and most recent activity year. Optionally filter by claimant state.

Input parameters:

- `alj_name` (string, required): ALJ full name or partial name
- `state` (string): Two-letter state code to filter by claimant state (optional)

### `eoir_judge_screen` (~59 tokens)

Profile an EOIR immigration judge. Returns grant rate, denial rate, removal rate, representation rate, represented grant rate, top courts, and top nationalities heard.

Input parameters:

- `judge_name` (string, required): Immigration judge full name or partial name

### `bva_screen` (~70 tokens)

Screen a veterans claim issue type at the Board of Veterans' Appeals. Returns allowance rate, denial rate, remand rate, and docket type distribution for the matched issue.

Input parameters:

- `issue_type` (string, required): Veterans claim issue type (e.g. PTSD, hearing_loss, TBI, back_pain)

### `securities_company_screen` (~59 tokens)

Screen a company for securities class action history using Stanford SCAC data. Returns total cases, dismissal rate, average and max settlement amounts, top circuits, and top case types.

Input parameters:

- `company` (string, required): Company name to screen for securities class actions

## Diagnostics

Captured diagnostic sections: Provenance, Dependencies. The full working is on the page: https://verifymcp.io/servers/mysplitifi-splitifi-mcp/splitifi-mcp#diagnostics

## Score history

- 2026-08-03: 60
- 2026-08-02: 60
- 2026-08-01: 20
- 2026-07-31: 20
- 2026-07-30: 46
- 2026-07-28: 46
- 2026-07-27: 46

## Links

- npm package: https://www.npmjs.com/package/splitifi-mcp
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- Changelog JSON feed: https://verifymcp.io/servers/mysplitifi-splitifi-mcp/splitifi-mcp/changelog.json
- HTML version of this page: https://verifymcp.io/servers/mysplitifi-splitifi-mcp/splitifi-mcp