Valuein — SEC EDGAR Fundamentals & Smart-Money Data

Approve a staged action by id and RUN the underlying tool call it proposed, using the caller's own current credentials — never the original proposer's. Idempotent and race-safe: an action already decided (approved by a concurrent call, rejected, executed, or failed) is NEVER re-executed — this returns the action's current state with `executed_now: false` instead. On a fresh approval, `executed_now` is true and `tool_result` carries the underlying tool's own structured result, exactly what a direct call to that tool would have returned. If the underlying tool itself fails, the staged action transitions to 'failed' with a `reason` — this call still succeeds (the approval + execution ATTEMPT is what it promises; a failed underlying write is a normal, inspectable outcome, not a tool error). An id belonging to a different customer's token is indistinguishable from an unknown id (returns NOT_FOUND) — ownership is never leaked. Tier: sp500+ (sample rejected).

Cancel a pending scheduled task by id (from schedule_task or list_scheduled_tasks). Only a `pending` task can be cancelled — one that already woke (completed) cannot be un-woken. Idempotent: cancelling an already-cancelled task is a no-op. Tier: sp500+ (sample rejected).

Compare a company's core financial metrics across two fiscal periods side-by-side. Shows absolute and percentage changes with significance classification (minor < 5%, notable 5–15%, significant > 15%). The response includes a `material_changes` count: this is the number of metrics whose `significance` ∈ {notable, significant} (i.e. absolute percentage change > 5%). Use it as a quick scalar to triage filings — anything > ~3 typically signals a material event worth deeper review. Use period format: 'FY2024' for annual, 'Q1-2024' for quarterly. Pass `period_a` as the EARLIER period and `period_b` as the LATER one — if you invert them the server auto-swaps and sets `swapped: true` in the response so deltas always carry the correct sign (rather than silently flipping). Point-in-time safe via as_of_date. Available on all plans.

M&A accretion/dilution: the standard sell-side/banker quick-screen for whether a proposed acquisition adds to (accretive) or subtracts from (dilutive) the acquirer's EPS in the first pro-forma year. Pulls net income + shares outstanding for both companies, and each side's latest EOD close (acquirer's price converts stock consideration into new shares issued; target's price is used only to disclose the offer premium). Caller sets the consideration mix (cash_pct, cash-financed by new debt or the acquirer's balance sheet), annual run-rate synergies, and the new-debt interest rate. A SINGLE pro-forma-year bridge — NOT a multi-year merger model; synergy ramp, integration costs, and purchase-price-allocation amortization (goodwill/intangibles step-up) are not modeled (see `result.caveats[]`). `result.accretion_dilution_pct` positive = accretive, negative = dilutive. Tier: sp500+.

Forward discounted-cash-flow valuation (two-stage Gordon-growth model): caller provides growth + WACC + terminal assumptions, returns per-share intrinsic value (`value_per_share_cents`, cents USD) + 5×5 sensitivity grid. Pulls FCF base + net debt + shares from R2; caller can override any field. Definitions (consistent with `get_financial_ratios` / `get_capital_allocation_profile`): FCF base = operating_cash_flow − capex (absolute USD); net_debt = total_debt − (cash + short-term investments). Shares resolve via a fallback chain (valuation row → fact CommonSharesOutstanding → net_income/eps_diluted), reported as `result.shares_source`. The pulled inputs are echoed in `result.inputs_echo` with their source lineage so the valuation is reproducible and traceable. A null `value_per_share_cents` means the model is degenerate (e.g. WACC ≤ terminal growth, or FCF base ≤ 0) or a required input was unavailable — it is NOT a zero valuation; the `reason` field explains. Use the returned figures exactly. Use this when you want to drive the assumptions yourself; for the pipeline's pre-computed DCF/DDM value and inputs (no assumptions needed) use `get_valuation_metrics` instead. Does NOT persist a report — use `create_report` (report_type:'reverse_dcf') for that. `fcf_source` (default "trend"): "trend" compounds a single FCF base by `stage1_growth_rate` every year (the original behavior, unchanged). "three_statement" instead runs a full linked Income Statement / Balance Sheet / Cash Flow projection (`project_three_statement`'s engine) and feeds its year-by-year FCF stream into the same PV math — `stage1_growth_rate` is then ignored (kept for echo only) because revenue growth + margins drive FCF instead of a flat compounding rate. The projection detail (including per-year `tie_out_ok`) is returned in `three_statement_detail` when used. Tier: sp500+.

Leveraged buyout returns analysis: caller provides entry/exit multiples, leverage, and a hold period; the tool builds a Day-1 pro-forma opening balance sheet from the deal's own sources & uses (cash-free, debt-free convention — entry_debt = leverage_multiple x EBITDA, sponsor_equity = entry_enterprise_value + minimum_cash - entry_debt), then runs it through the same linked three-statement engine as `project_three_statement` (100% FCF-to-debt-paydown sweep by default). Returns MOIC and IRR (solved by bounded bisection over the sponsor's cash flow stream — interim dividends if any, plus exit equity proceeds). EBITDA is PROXIED by operating income (no separate D&A concept exists in the dataset) unless entry_ebitda_override is supplied — see `result.entry_ebitda_is_proxy`. `result.irr.converged:false` means no root was found (e.g. a total wipeout) — never a fabricated rate. Every simplification is listed in `result.caveats[]`. Tier: sp500+.

Persist an alert and register it with the firing pipeline. Five condition shapes: * `filing_event` — fire when a ticker files a chosen form type (8-K, 10-K, etc.). * `ratio_threshold` — fire when a ticker's financial ratio crosses a threshold (e.g. interest_coverage < 1.5). * `watchlist_change` — fire on any filing on any ticker in a named watchlist. * `price_move` (Pro+) — fire when a ticker's close-to-close move over 1/5/21 trading days crosses a percent threshold in a given direction. * `fundamental_change` (Pro+) — fire when a standard_concept reports a brand-new period or gets restated. Delivery channels: `email` (transactional via Resend), `webhook` (HMAC-SHA256-signed POST), `slack` (hooks.slack.com incoming webhook), `dashboard` (in-app inbox), or `agent_run` (Pro+ — runs a standing agent team and delivers the finished artifact to your inbox). The cron evaluator runs every 5 minutes. Use `test_alert` to verify your channel is wired correctly before relying on the cron.

Synchronously generate a research report and persist it under the caller's authorship. Two subtypes: • `reverse_dcf` — solves the stage-1 free-cash-flow growth rate the market price implies, with a 5×5 sensitivity grid across WACC × terminal-growth assumptions. Returns full markdown + structured JSON + every numerical claim's citation chain to the originating SEC accession. • `thesis` — snapshot a saved thesis (via `save_thesis`) as a frozen narrative report with at-a-glance table, author notes, anchor fundamentals (latest annual), and lineage to the source filing. Later edits to the thesis do NOT propagate — generate a new report to capture new state. Tier: sample tier rejected — reports are per-author state.

Persist a trigger -> action rule and register it with the evaluator. 7 trigger types accepted (alert_fired, schedule_tick, inbox_item, price_threshold, filing_event, manual, scheduled_task_wake) x six action types (run_team, send_alert, create_report, score_thesis, schedule_task, post_inbox). These trigger types have a live event source and DO dispatch today: alert_fired, schedule_tick, inbox_item, filing_event and scheduled_task_wake. price_threshold and manual are accepted and persisted (forward-compatible schema) but have NO live event source wired yet, so a rule created with one of them is saved as enabled:true and simply never fires. Always read the returned rule's `trigger_wiring_status` field ("live" vs "not_yet_wired") — it is computed from the dispatcher's own registry, so it is authoritative even if this description is stale. `condition_expr` is an OPTIONAL single comparison (`"field op value"`, op one of gt/gte/lt/lte/eq, e.g. `"price_change_pct gt 5"`) evaluated against the trigger event's payload — omit to fire on the trigger alone. Deliberately NOT a general expression language (no AND/OR, no loops) — this is both an anti-complexity and an anti-loop guard; compose multiple rules if you need more than one comparison. Use `test_rule` immediately after creating to verify it fires as expected WITHOUT spending a real dispatch. Tier: sp500+ (sample rejected).

Forget ONE durable memory entry by key — use it when a note you stored is now wrong, superseded, or was only ever scratch. Every entry is re-read into your context at the start of every future run, so leaving a stale one behind means re-grounding yourself in something false; deleting is the correction. Idempotent: deleting a key that is not there returns deleted:false, not an error. Also how you free a slot when the 200-entry cap is reached. This removes only YOUR memory note — it never touches a thesis, claim, report, or any financial fact. Tier: sp500+ (sample rejected).

Soft-delete an alert by its id (from create_alert/list_alerts): status flips to `deleted` and it is removed from the cron evaluator index so it stops firing. Alerts are immutable — to change one, delete then create_alert. Idempotent. Tier: sp500+ (sample rejected).

Remove a user-authored citation correction by fact_id. Idempotent — deleting a missing override returns deleted=false without error. Once deleted, reports that previously rendered the corrected value revert to the canonical fact value on next regeneration. Tier: paid + free (sample rejected).

Soft-delete a claim by id. The row and its score history are preserved for audit (archived, not erased); the claim drops out of default list_claims results. Idempotent — deleting an already-archived claim succeeds. Tier: all paid + free tiers (sample rejected).

Soft-delete a report owned by the caller: status flips to `delisted`, visibility to `private` — not a hard delete, the row and R2 artifact are preserved (90-day audit window). Idempotent (deleting an already-delisted report succeeds). Sample tier rejected.

Delete a rule by id (from create_rule/list_rules) — removes it from both the catalog and the evaluator's scan index, so it stops firing immediately. Rules are immutable — to change one, delete then create_rule. Idempotent. Tier: sp500+ (sample rejected).

Soft-delete a saved thesis: status flips to `archived` (the row stays for audit / re-scoring). Idempotent — archiving an already-archived thesis succeeds. Hard-delete is not supported by design; future versions may expire archived theses after N years. This does not delete the claims linked to the thesis — use delete_claim for those. Tier: paid + free (sample rejected).

Delete an uploaded document before its 24h TTL. Deleting a missing/already-expired/foreign id returns deleted:false rather than an error.

Soft-delete a watchlist by its name (not id): status flips to `archived` (still readable via list_watchlists status=all/archived). The name is freed for reuse by a new save_watchlist. Idempotent. Tier: sp500+ (sample rejected).

Returns the Parquet schema for all tables in the Valuein SEC data warehouse. Includes table descriptions, column names, types, primary keys, and foreign-key references. Use this tool to understand the data model before querying with other tools. No data reads required — schema is embedded in the manifest. Available on all plans.

Soft-delete a single inbox item by its id (from list_alert_inbox) — not an alert id; sets `dismissed_at`. The row stays queryable via `list_alert_inbox(include_dismissed=true)` for audit. Idempotent. Tier: sp500+ (sample rejected).

Deterministic forensic-accounting scores for a single ticker: partial Beneish M-Score, Sloan accruals, and a solvency snapshot. Returns a red-flag narrative ranked by severity, with citations to source filings. Used by the `forensic_earnings_brief` SOP. Note: full Beneish needs AR / current assets / PPE / SGA / current liabilities, which aren't in our fundamentals model. We compute the recoverable subset (SGI + TATA + LVGI) and flag `partial=true`. Tier: sp500+.

Render a peer comparables table into an Excel workbook. The Comps sheet is formatted as a named Excel Table (`ValueinPeerComps`) so the user gets one-click Insert Chart on any column — the cleanest workaround for not embedding chart objects server-side. Subject-row highlight makes side-by-side comparison instant. A Summary sheet adds subject vs peer-median deltas. SERVER-TRUST: the ratios you pass are rendered as-supplied and are NOT re-derived by Valuein, so the workbook carries a visible 'figures supplied by caller, not verified by Valuein' watermark (response `verification.status` = 'unverified'). For authoritative numbers, source them from `get_peer_comparables` / `get_financial_ratios` first. Pair with `get_peer_comparables` for a typical flow. Tier: pro+.

Render a forward DCF result into a professional Excel workbook (Summary + 5×5 Sensitivity heatmap + Inputs sheet). Native conditional formatting — no chart images needed. Returns a 15-minute presigned R2 download URL. SERVER-TRUST: the DCF is re-derived in-Worker from the supplied `inputs_echo` (the math is pure + deterministic) and the workbook renders Valuein's recomputed figures — never the caller's claimed values. If the claimed figures disagree, the workbook is still produced but stamped with a visible correction banner and the response `verification.status` is 'corrected'. A fabricated per-share value can never appear as Valuein-authoritative. Pair with `compute_dcf` for a typical analyst flow: agent calls `compute_dcf({ticker, ...})`, then passes the structured result straight to `generate_dcf_xlsx({ticker, dcf_result, ...})` to materialise a shareable file. Tier: pro+.

Render an LBO result into a professional Excel workbook (Summary + year-by-year Projection table + Inputs sheet). Returns a 15-minute presigned R2 download URL. SERVER-TRUST: the deal is re-derived in-Worker from the supplied `lbo_result.inputs_echo` (the math is pure + deterministic) and the workbook renders Valuein's recomputed figures — never the caller's claimed values. If the claimed figures disagree, the workbook is still produced but stamped with a visible correction banner and the response `verification.status` is 'corrected'. Pair with `compute_lbo` for a typical flow: agent calls `compute_lbo({ticker, ...})`, then passes the structured result straight to `generate_lbo_xlsx({ticker, lbo_result, ...})` to materialise a shareable file. Tier: pro+.

Render a structured research brief into a professionally-styled Word document — a cover page (title as the hero, the named analyst credited directly beneath it, a small 'Built on Valuein' credit linked to valuein.biz) followed by page 2 (masthead repeating the analyst's name, abstract, optional snapshot table, body sections, and a citations table with clickable SEC EDGAR links), with a running footer (ticker, page number, a single disclosure line) repeated on every page. No embedded charts in v1; pair with `generate_dcf_xlsx` / `generate_comps_xlsx` for visuals the analyst pastes in. SERVER-TRUST: prose, snapshot rows, and citations are rendered as-supplied and are NOT verified by Valuein, so the brief carries a visible 'figures supplied by caller, not verified by Valuein' watermark (response `verification.status` = 'unverified'). Resolve each citation via `verify_fact_lineage` before publishing. Consumes the same `sections` + `citations` shape `create_report` emits, so the typical flow is two tool calls: `create_report` → `generate_research_brief_docx`. Tier: pro+.

Recall this user's durable memory. Omit `key` (or pass null) to read EVERYTHING you have remembered, newest-first — do this at the START of a task to re-ground yourself. Pass a specific `key` to fetch one entry. An absent key returns an empty list, never an error (absence is a first-class answer). Tier: sp500+ (sample rejected).

Fetch full detail for one of the caller's own standing-agent runs by id (from list_agent_runs) — status, goal, tickers, cost, artifact ids, role breakdown, and any error. A run may have been triggered by this same agent or by the customer's own Workspace; this tool works either way. Returns `found: false` (not an error) for an unknown id OR an id belonging to another customer — there is no distinguishing signal, by design. Tier: sp500+ (sample rejected).

Returns SC 13D / SC 13G blockholder disclosures (5%+ stakes) for a US public company. Each row carries percent_owned, sole/shared voting + dispositive split, schedule_type, and the first-class ``going_active`` flag — TRUE when the same filer flipped 13G → 13D within the lookback window (the single most actionable activist signal in this dataset). Use latest_only=true (default) to dedupe to the most recent filing per filer. Use collapse_groups=true to fold multi-person filings into one row. Institutional tier only.

Get a multi-year capital allocation breakdown for a US public company. Shows how management deploys cash across all six categories — capex, R&D, M&A, dividends, buybacks, and debt — plus pre-computed deployment ratios (% of operating cash flow) and over-distribution flags. Use this tool when the user asks: how does a company allocate capital, what's the buyback-vs-dividend mix, is the company over-distributing, is growth funded by R&D or M&A, what's the cash-return-ratio trend, or any 'where does the money go' question — including owner-earnings (Buffett-style) and reinvestment-rate (Damodaran-style) analysis. Data sourced from annual 10-K filings; PIT-safe via as_of_date. R&D is included as a deployment category (the primary growth-reinvestment vehicle for knowledge-economy firms), but since it's already deducted before operating cash flow, `rd_pct_ocf` is INFORMATIONAL and `total_deployment_pct_ocf` EXCLUDES R&D to preserve the cash-flow identity (OCF = capex + M&A + dividends + buybacks + debt repayment + Δcash). The `flags` object carries pre-computed booleans: `buybacks_exceed_fcf`, `total_returns_exceed_fcf` (buybacks + dividends > FCF), and `debt_funded_distribution` (over-distribution funded by leverage vs cash). Available on all plans.

Fetch a single claim by id, plus the ids of theses it supports/refutes and its full append-only score history. Use this to inspect a claim's evidence, current status, and how its outcome has evolved. Tier: all paid + free tiers (sample rejected).

Retrieve standardized SEC EDGAR fundamental financial metrics for a US public company. Returns revenue, gross profit, operating income, net income, EPS (diluted), total assets, total liabilities, stockholders' equity, cash & equivalents, total debt, operating cash flow, and capital expenditures for one or more fiscal periods. Data sourced from 10-K (annual) and 10-Q (quarterly) filings. Point-in-time: no look-ahead bias — pass `as_of_date` (YYYY-MM-DD) to reconstruct exactly the information set known on that date. This returns the raw as-reported line items ONLY. Do NOT derive metrics from them yourself — a hand-computed figure carries no fact_id and cannot be verified against a filing. Every derived metric is already served pre-computed WITH provenance: free cash flow, FCF margin, margins, ROE/ROA/ROIC, leverage and the price multiples come from `get_valuation_metrics`; the full ratio table (incl. per-share, owner-earnings, growth) from `get_financial_ratios`; intrinsic value from `compute_dcf`. If one of those is gated on your plan, say so and offer the upgrade — never substitute your own arithmetic.

Returns a short-lived (15-min) download URL for a bulk Parquet object that can be piped directly into Python/DuckDB/Polars for high-throughput computation that exceeds the MCP context window. The URL streams the object straight from Valuein storage and supports HTTP range reads, so `duckdb.read_parquet(url)` / `pl.read_parquet(url)` work without downloading the whole file first. Datasets: fact (per-entity partition — requires ticker), ratio (all computed ratios), valuation (DCF inputs), filing (SEC filing metadata), references (company universe), index_membership (historical index composition). Scoped to the caller's tier bucket; the link is signed and cannot be used to list the bucket or read other objects.

Reported earnings results and a model-derived earnings-trend signal for a company, by fiscal period: actual reported EPS, a trailing-trend EPS estimate (`eps_trend_est`), the deviation of actual vs that trend (`eps_surprise_pct`), reported revenue, and year-over-year revenue growth. IMPORTANT: `eps_trend_est` is NOT Wall Street analyst consensus — Valuein is sourced purely from SEC EDGAR and carries no consensus feed. It is a deterministic estimate computed from the company's own prior reported EPS, so `eps_surprise_pct` measures how far the print landed from its own trailing trend, not whether it 'beat the Street'. Use it to track earnings/revenue trajectory and momentum, not to claim a consensus beat or miss. Point-in-time safe — pass as_of_date to filter by SEC acceptance (accepted_at) for look-ahead-free backtests. Available on all plans.

Get pipeline-computed financial ratios from ratio.parquet. Served categories: profitability (margins, ROE, ROA, ROIC), liquidity (current ratio, quick ratio), leverage (D/E, interest coverage, net debt/EBITDA), efficiency (asset turnover, inventory days), per_share (EPS, BVPS, FCF/share), owner_earnings (Buffett FCF, owner yield), valuation (pe_ratio, pb_ratio, ev_ebitda, market_cap, dividend_yield), and the pipeline-emitted forensic, growth, and rank (cross-sectional *_sector_pctile) categories. NOT every category exists for every ticker — omit `categories` to get whatever this ticker has, or read `available_categories` in the CATEGORY_NOT_AVAILABLE envelope. valuation is LIVE (schema 2.18.0): price-derived multiples from EOD prices period-end-aligned — pipeline-derived, NOT strictly PIT (no accepted_at column on these rows). Includes TTM rows alongside annual; each row's `is_calendar_aligned` is TRUE only when period_end sits on the fiscal-year boundary (±7 days) — filter to TRUE when joining ratios to fact-table fundamentals on (entity, fiscal_year). For historical cuts use `as_of_date` (PIT by accepted_at when present, else by period_end — see the param). Use this *instead of* `get_valuation_metrics` when you only need ratios (no DCF wiring); use `get_valuation_metrics` when you also need DCF/DDM. Each ratio is a `{value, unit, category, reason}` entry with a response-level `lineage` (DerivedLineage) pointing to `get_company_fundamentals` / `verify_fact_lineage` for filing-level provenance; a null value carries a `reason` (e.g. INPUT_MISSING) so missing is never a real zero. Available on all plans.

Role-weighted insider sentiment score on a fixed [-100, +100] scale for a single issuer over a lookback window. Role weights: CEO/CFO = 3.0 (via officer_title pattern), other NEO Officer = 2.0, 10%-Owner = 1.5, Director = 1.0. P = +1, S = -1; option exercises, grants, and tax withholdings are neutralised. Cluster flag = TRUE when ≥3 distinct insiders transacted within any 30-day window inside the lookback. Institutional tier only.

Form 3 / 4 / 5 / 144 line items for a US public company. Returns each transaction (or initial holding / proposed sale) with the insider's name, role, transaction code, share count, price, and notional. Filters by lookback window, transaction code (P=purchase, S=sale, A=grant, M=option exercise, F=tax withholding, etc.), insider role, and minimum share threshold. Institutional tier only — sample / sp500 / pro return ENTITLEMENT_DENIED with an upgrade link.

Returns top-N institutional holders of a US public company at a specific period_end (latest by default), with aggregate institutional shares, total market value, holder count, and HHI concentration (sum of squared share-of-total percentages). Sourced from Form 13F-HR via the by-issuer partition. Institutional tier only. 13F filings carry a ~45-day reporting lag — staleness_warning fires when latest data is older than 90 days.

Returns a 13F filer's full portfolio at a specific period_end (latest by default), with QoQ deltas vs the prior quarter (new / increased / decreased / exited / unchanged). Specify the filer either by filer_cik (preferred) or filer_name (fuzzy match against entity.name; multiple matches raise an ambiguity error so you can disambiguate by CIK). Institutional tier only.

Read the caller's Morning Brief — a daily AI-generated market digest covering overnight moves across the customer's own watchlists and theses, produced by the Workspace. Omit `day` to get the most recent brief available (not necessarily today's); pass a specific `day` (YYYY-MM-DD) to fetch that day's brief. It is normal for no brief to exist yet if the customer hasn't set up or recently generated one — that returns `found: false`, not an error. Tier: sp500+ (sample rejected).