ideaudit
NPM · @INITE/IDEAUDIT-TOOLS · 2 COMPONENTS · SCANNED SEP 25
The scoring behind an audit allowed to say no. Twenty deterministic tools, offline, no account.
Available components
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. How we score → Why this is hard to score →
Supply Chain Security98
- No malware found by supply-chain analysis.Pass
- No known CVEs affecting this package version or its production dependencies.Pass
- No install/post-install scripts declared.Pass
- 31 of 95 dependencies flagged as unhealthy. View diagnostics → Partial
Provenance & Transparency45
- Source repository is publicly reachable at the declared URL. View diagnostics → Pass
- Provenance check failed: no build-provenance attestation is published. See how to fix → View diagnostics → Fail
- Clear OSI-approved license (Apache-2.0).Pass
- Actively maintained (last published 19 days ago).Pass
- Disclosure check failed: no security disclosure policy was found in the source repository. See how to fix → Fail
Schema Quality & AI Usability65
- AI-judged instruction clarity (good).Pass
- Context-footprint check failed: tool/resource definitions use about 2371 tokens (~118/item across 20 items; 20 tools + 0 resources), over budget; trim descriptions and params. See how to fix → Fail
- Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management63
- Stability observed for 19 of 30 days with no destabilising changes; credit accrues until the full window elapses.Partial
Tool Coverage73
- 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
- 18% of tool parameters carry a description.Partial
Tool Safety75
- No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
- 0 of 1 tool(s) whose name or description implies an irreversible operation declare an MCP destructiveHint annotation; "derive_kill_criteria" implies "kill" and declares no destructiveHint at all, which the MCP spec reads as destructive by default. See how to fix → Fail
- An AI judge read all 20 captured unit(s) of tool text and found none that tries to manipulate the model reading it.Pass
Capabilities100
- Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.Pass
How do I install the ideaudit MCP server?
ideaudit runs locally as an npm package, launched with npx -y @inite/ideaudit-tools. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.
npm · @inite/ideaudit-tools
claude mcp add studio-inite-ideaudit-tools -- npx -y @inite/ideaudit-tools
{
"mcpServers": {
"studio-inite-ideaudit-tools": {
"command": "npx",
"args": [
"-y",
"@inite/ideaudit-tools"
]
}
}
} {
"servers": {
"studio-inite-ideaudit-tools": {
"command": "npx",
"args": [
"-y",
"@inite/ideaudit-tools"
]
}
}
} codex mcp add studio-inite-ideaudit-tools -- npx -y @inite/ideaudit-tools
{
"$schema": "https://opencode.ai/config.json",
"mcp": {
"studio-inite-ideaudit-tools": {
"type": "local",
"command": [
"npx",
"-y",
"@inite/ideaudit-tools"
],
"enabled": true
}
}
} openclaw mcp add studio-inite-ideaudit-tools --command npx --arg -y --arg @inite/ideaudit-tools
mcp_servers:
studio-inite-ideaudit-tools:
command: "npx"
args: ["-y", "@inite/ideaudit-tools"] {
"McpServers": {
"studio-inite-ideaudit-tools": {
"Transport": "stdio",
"Command": "npx",
"Arguments": [
"-y",
"@inite/ideaudit-tools"
]
}
}
} assistant mcp add studio-inite-ideaudit-tools -t stdio -c npx -a -y @inite/ideaudit-tools
{
"mcpServers": {
"studio-inite-ideaudit-tools": {
"command": "npx",
"args": [
"-y",
"@inite/ideaudit-tools"
]
}
}
} Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.
- 25 Sept 26 0
- We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
- 24 Sept 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 57 to 60. That category is still filling its 30-day observation window: 17 days of observed history at the previous scan, 18 at this one. The score rises as the window fills, whether or not the server changes.
- 22 Sept 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 50 to 53. That category is still filling its 30-day observation window: 15 days of observed history at the previous scan, 16 at this one. The score rises as the window fills, whether or not the server changes.
- 20 Sept 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 43 to 47. That category is still filling its 30-day observation window: 13 days of observed history at the previous scan, 14 at this one. The score rises as the window fills, whether or not the server changes.
- 17 Sept 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 33 to 37. That category is still filling its 30-day observation window: 10 days of observed history at the previous scan, 11 at this one. The score rises as the window fills, whether or not the server changes.
- 15 Sept 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 27 to 30. That category is still filling its 30-day observation window: 8 days of observed history at the previous scan, 9 at this one. The score rises as the window fills, whether or not the server changes.
- 13 Sept 26 +4
- Stability: unverified → 0.23 ▲ functional
- 6 Sept 26 64
First indexed and scored.
Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.
Captured 25 Sept 2026 · Analysed npm/@inite/ideaudit-tools@1.0.0
Provenance No attestation
The registry publishes no build provenance for this version, so there is nothing to verify.
| Result | No attestation |
|---|---|
| Ecosystem | npm |
Background: How many MCP packages publish verified provenance →
Dependencies 95 packages
| Packages resolved | 95 |
|---|---|
| Stale | 31 |
| Tree resolution | Complete |
Background: SBOMs and build attestations, explained →
The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability. A tool's description is untrusted text the model reads on every call, which is what makes this list a security surface and not just an inventory: how tool poisoning works →
compute_barrier ~70
Compute barrier_score (0-24) + label (PRISTINE/OPEN/COMPETITIVE/CROWDED) from competitor counts + SERP noise fraction.
| Name | Type | Req | Description |
|---|---|---|---|
| adjacentCompetitorCount | integer | – | – |
| directCompetitorCount | integer | yes | – |
| serpNoise | number | – | – |
No output schema declared.
No examples provided.
compute_budget_proof ~90
Compute budget_proof_score (0-10) + label (STRONG/CONFIRMED/WEAK/ABSENT) + purchase_intent_pct from pricing hits + review-site hits + intent mentions.
| Name | Type | Req | Description |
|---|---|---|---|
| hasNamedPricing | boolean | – | – |
| pricingHitsCount | integer | yes | – |
| purchaseIntentMentions | integer | – | – |
| reviewSiteHitsCount | integer | – | – |
No output schema declared.
No examples provided.
compute_build_complexity ~79
Compute build_complexity_penalty (0-10, higher = worse) + per-factor breakdown. Hard tags: ml/realtime/blockchain/hardware/compliance/custom-ai/regulated/on-device-ai/iot.
| Name | Type | Req | Description |
|---|---|---|---|
| externalApisCount | integer | yes | – |
| integrationsCount | integer | – | – |
| stackComplexityTags | array | – | – |
No output schema declared.
No examples provided.
compute_collection_scores ~61
Compute 12 deterministic collection scores (0-100) + badges + death reason for an enriched idea. Pure math. No external calls.
| Name | Type | Req | Description |
|---|---|---|---|
| analysisId | string | yes | – |
| enrichedData | object | yes | EnrichedData with canonical_idea signals. |
No output schema declared.
No examples provided.
compute_crossed_matrix ~184
Crossed-product audit explorer. Same input as compute_dealbreakers_v2 — returns substrate verdict (no-observer baseline) + crossed verdict (when observer supplied) + a 5-row matrix of {solo, cofounded_technical, cofounded_business, domain_expert, serial} archetype verdicts. Never persists; meant for the dashboard "view as [archetype]" dropdown and for previewing a verdict before committing to it.
| Name | Type | Req | Description |
|---|---|---|---|
| hasMajorContradiction | boolean | – | – |
| lensScores | array | yes | – |
| observer | object | – | Founder profile that crosses with the substrate idea to produce an observer-relative verdict. When omitted, only the substrate verdict is returned. |
| sector | string | – | – |
| stage | string | yes | – |
| stageProbabilities | object | – | – |
| unresolvedContradictions | integer | – | – |
No output schema declared.
No examples provided.
compute_dealbreakers_v2 ~200
Methodology v2 dealbreakers — stage-aware weights + confidence-weighted lens scoring + risk-asymmetric verdict (GO requires score≥80 AND zero red flags AND avg confidence≥0.6). Optional `observer` triggers the crossed-product pipeline: substrate verdict (no-observer baseline) PLUS crossed verdict (observer-perturbed weights, risk-tolerance shifted thresholds) PLUS 5-row archetype matrix. The KILL gate (≥2 blockers / score<50) is observer-invariant — fatal stays fatal.
| Name | Type | Req | Description |
|---|---|---|---|
| hasMajorContradiction | boolean | – | – |
| lensScores | array | yes | – |
| observer | object | – | Founder profile that crosses with the substrate idea to produce an observer-relative verdict. When omitted, only the substrate verdict is returned. |
| sector | string | – | – |
| stage | string | yes | – |
| stageProbabilities | object | – | – |
| unresolvedContradictions | integer | – | – |
No output schema declared.
No examples provided.
compute_funding_momentum ~62
Compute funding_momentum_score (0-10) + badge (HOT/WARM/COOL/COLD) from tier-weighted funding-article hit counts.
| Name | Type | Req | Description |
|---|---|---|---|
| hitsByTier | object | yes | – |
| recent30dHits | integer | – | – |
No output schema declared.
No examples provided.
compute_hiring_demand ~47
Compute hiring_demand_score (0-10) from priority-weighted ATS site hit counts (use registries/hiring-sources for priorities).
| Name | Type | Req | Description |
|---|---|---|---|
| sites | array | yes | – |
No output schema declared.
No examples provided.
compute_lrs_composite ~113
Compose lrs_final_100 (0-100) + label (WEAK/EMERGING/GOOD/STRONG/ELITE) + leaderboard_eligible flag + sub-percent breakdown. Weights: sv 0.25, sp 0.30, barrier 0.25, monetization 0.20.
| Name | Type | Req | Description |
|---|---|---|---|
| barrierScore | number | yes | – |
| monetizationScore | number | yes | – |
| searchVelocityScore | number | yes | – |
| socialPainScore | number | yes | – |
No output schema declared.
No examples provided.
compute_lrs_composite_v2 ~256
LRS composite v2 — 6 components (SV, Pain, Barrier, Monet, X-Signal, Budget-Proof). Default Python weights 0.18/0.22/0.18/0.14/0.18/0.10 sum=1.0. Returns BOTH weighted score and equal-weight baseline (per OECD Handbook + Greco 2018 — equal-weight is defensible default when no outcome calibration exists). buildComplexityPenalty 0-10 subtracted from score. sectorProfile (ai_native/creator/crypto) opt-in reshuffles SV→0.16, X→0.20. Labels: THE_ROAR (≥80) / PROMISING (≥60) / EXPERIMENTAL (≥40) / WEAK_SIGNAL (<40).
| Name | Type | Req | Description |
|---|---|---|---|
| barrierScore | number | yes | – |
| budgetProofScore | number | yes | – |
| buildComplexityPenalty | number | – | – |
| monetizationScore | number | yes | – |
| searchVelocityScore | number | yes | – |
| sectorProfile | string | – | Opt-in sector weight override. Default uses Python canonical weights. |
| socialPainScore | number | yes | – |
| xSignalScore | number | yes | – |
No output schema declared.
No examples provided.
compute_monetization ~83
Compute monetization_score (0-21) + label + has_pricing_anchors from pricing anchors + model tags + deal cycle hint.
| Name | Type | Req | Description |
|---|---|---|---|
| dealCycle | string | – | instant/days/weeks/months/quarters |
| modelTags | array | – | e.g. ["subscription","usage","marketplace"] |
| pricingAnchorsCount | integer | yes | – |
No output schema declared.
No examples provided.
compute_multi_source_tam ~117
Multi-source TAM consensus. Pass 2-3 sources of market-size text. Optional `estimateYear` per source — when supplied, the result includes yearRange and a hasStaleData flag (true if the span exceeds 5 years). Outliers are dropped by modified Z-score over the median absolute deviation when n≥4. Returns the extracted dollar amounts + consensus median + an agreement score 0..1, where 1 means every source lands within 20% of the median.
| Name | Type | Req | Description |
|---|---|---|---|
| inputs | array | yes | – |
No output schema declared.
No examples provided.
compute_ppc_spend_signal ~118
Wave 5 N.4 — compute ppc_spend_score (0-10) + label (STRONG/CONFIRMED/WEAK/ABSENT) + market_saturation from PPC traffic projection (avgCpcUsd, totalMonthlySpendUsd, optional competitorBidders + competition). Feed numbers from dataforseo_ad_traffic.
| Name | Type | Req | Description |
|---|---|---|---|
| avgCpcUsd | number | yes | – |
| competition | number | – | – |
| competitorBidders | integer | – | – |
| totalMonthlySpendUsd | number | yes | – |
No output schema declared.
No examples provided.
compute_search_velocity ~74
Compute search_velocity_score (0-25) from Trends timeline values + rising queries count + geo region count.
| Name | Type | Req | Description |
|---|---|---|---|
| geoRegionCount | integer | – | – |
| risingQueriesCount | integer | – | – |
| timelineValues | array | yes | Monthly Trends values 0-100 (e.g. last 10-12 months). |
No output schema declared.
No examples provided.
compute_search_velocity_v2 ~270
Search velocity (0-25) v2 — canonical 0.40*volume + 0.30*trend + 0.20*intent + 0.10*geo. CRITICAL: externalVolumeNorm MUST come from external sources (Amazon BSR / app store installs / job-board postings) — NOT the Trends timeline (would double-count, since Trends is itself normalized 0-100 within window). trendNorm is derived internally from trendsTimelineValues. Trends peak<50 zeroes the trend component (Yotpo SEO floor). Optional daysSinceLastSignal applies exponential freshness decay (search half-life 90d).
| Name | Type | Req | Description |
|---|---|---|---|
| daysSinceLastSignal | number | – | Optional: days since most recent confirming signal. Triggers exponential freshness decay (half-life 90d). |
| externalVolumeNorm | number | yes | Normalized 0-1 demand volume from EXTERNAL sources (Amazon, app stores, jobs). Caller normalizes before passing. |
| geoSpreadNorm | number | yes | 0-1 geographic spread (regions with interest > threshold). |
| intentNorm | number | yes | 0-1 commercial/transactional intent ratio. |
| trendsTimelineValues | array | yes | Monthly Trends values 0-100. Used ONLY to derive trendNorm — never as raw volume. |
No output schema declared.
No examples provided.
compute_social_pain ~70
Compute social_pain_score (0-30) + total mentions + dominant perspective (business/consumer/trend/mixed).
| Name | Type | Req | Description |
|---|---|---|---|
| categoryCounts | object | – | – |
| intentMentions | integer | – | – |
| painMentions | integer | yes | – |
| urgencyMentions | integer | – | – |
No output schema declared.
No examples provided.
compute_urgency_composite ~80
Compose composite_urgency_score (0-10) + badge (LOW/MEDIUM/HIGH/VERY_HIGH/EXTREME) from 3 sub-scores: news, pain, hiring.
| Name | Type | Req | Description |
|---|---|---|---|
| hiringSignalScore | number | yes | – |
| newsSignalScore | number | yes | – |
| painSignalScore | number | yes | – |
No output schema declared.
No examples provided.
compute_x_signal ~75
Compute x_signal_score (0-20) + recency share + positivity rate from X/Twitter mention counts.
| Name | Type | Req | Description |
|---|---|---|---|
| founderMentions | integer | – | – |
| mentionsCount | integer | yes | – |
| recent7dCount | integer | – | – |
| sentimentNegative | integer | – | – |
| sentimentPositive | integer | – | – |
No output schema declared.
No examples provided.
derive_kill_criteria ~139
Derive a falsifiable, data-driven list of kill criteria from upstream signals — the outputs of validate_unit_economics and compute_dealbreakers_v2, plus an ICP drift count. Returns one row per rule with {rule, threshold, status, evidence?}, where status is tripped_now / monitor / cleared. Replaces prose kill criteria, which are tautologies that can never fire.
| Name | Type | Req | Description |
|---|---|---|---|
| dealbreakers | object | – | The result of compute_dealbreakers_v2. |
| icpDriftCount | integer | – | – |
| unitEcon | object | – | The result of validate_unit_economics. |
No output schema declared.
No examples provided.
validate_unit_economics ~183
Sanity-check a unit-economics row before publishing it in a business-model slide. Catches the math-drift class of failures (customers × ARPU ≠ revenue), enforces the LTV/CAC ≥ 1.5 floor, the cohort-positivity check, and CAC payback bounds. Returns {ok, errors[{rule, severity, detail}], derived{ratios}}. Skills MUST regenerate the row when ok=false (block-severity errors); warn-severity errors should be surfaced in the final report but do not gate publication. No LLM calls.
| Name | Type | Req | Description |
|---|---|---|---|
| annualRevenue | number | yes | – |
| arpu | number | yes | – |
| cac | number | – | – |
| customers | number | yes | – |
| grossMargin | number | – | – |
| ltv | number | – | – |
| monthlyChurn | number | – | – |
No output schema declared.
No examples provided.
What is the ideaudit MCP server?
ideaudit is an MCP server listed in the public MCP registry as studio.inite/ideaudit-tools. The scoring behind an audit allowed to say no. Twenty deterministic tools, offline, no account. This page covers its npm package (@inite/ideaudit-tools).
Is the ideaudit MCP server safe to use?
ideaudit scores 73 out of 100 on VerifyMCP. We found no known CVEs affecting it as of 25 September 2026. It declares no install or post-install scripts. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.
What tools does the ideaudit MCP server expose?
ideaudit exposes 20 tools: compute_barrier, compute_budget_proof, compute_build_complexity, compute_collection_scores, compute_crossed_matrix, and 15 more. Their descriptions and schemas cost roughly 2,371 tokens of context every time the server is loaded.
Is the ideaudit MCP server still maintained?
ideaudit is still listed as active in the MCP registry. We last reached this channel on 25 September 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.
What licence is the ideaudit MCP server under?
ideaudit declares the Apache-2.0 licence, which is OSI-approved. That covers the source only, and says nothing about the cost of any service it calls.