{
  "data": {
    "tool": {
      "category": "",
      "endpoint": "https://api.inite.studio/mcp",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/inite-ideaudit-tools.json",
      "kind": "mcp",
      "listed": "indexed",
      "liveUrl": "https://www.anchorterminal.com/api/v1/live/inite-ideaudit-tools.json",
      "markdownUrl": "https://www.anchorterminal.com/tools/inite-ideaudit-tools.md",
      "mcpTools": {
        "check": {
          "checker": "anchor-check/1.0",
          "totalTokens": 4112,
          "counts": {
            "error": 0,
            "note": 1,
            "warn": 42
          },
          "findings": [
            {
              "rule": "TC11",
              "severity": "warn",
              "tool": "compute_barrier",
              "message": "none of its 3 parameters has a description",
              "fix": "Describe each one: format, units, an example, and what happens when it's left out."
            },
            {
              "rule": "TC11",
              "severity": "warn",
              "tool": "compute_budget_proof",
              "message": "none of its 4 parameters has a description",
              "fix": "Describe each one: format, units, an example, and what happens when it's left out."
            },
            {
              "rule": "TC11",
              "severity": "warn",
              "tool": "compute_build_complexity",
              "message": "none of its 3 parameters has a description",
              "fix": "Describe each one: format, units, an example, and what happens when it's left out."
            },
            {
              "rule": "TC11",
              "severity": "warn",
              "tool": "compute_collection_scores",
              "message": "1 parameter without a description: analysisId",
              "fix": "Describe each one: format, units, an example, and what happens when it's left out."
            },
            {
              "rule": "TC11",
              "severity": "warn",
              "tool": "compute_crossed_matrix",
              "message": "none of its 7 parameters has a description",
              "fix": "Describe each one: format, units, an example, and what happens when it's left out."
            },
            {
              "rule": "TC11",
              "severity": "warn",
              "tool": "compute_dealbreakers_v2",
              "message": "none of its 7 parameters has a description",
              "fix": "Describe each one: format, units, an example, and what happens when it's left out."
            },
            {
              "rule": "TC11",
              "severity": "warn",
              "tool": "compute_funding_momentum",
              "message": "none of its 2 parameters has a description",
              "fix": "Describe each one: format, units, an example, and what happens when it's left out."
            },
            {
              "rule": "TC11",
              "severity": "warn",
              "tool": "compute_hiring_demand",
              "message": "4 parameters without a description: sites, sites[].domain, sites[].hits, sites[].priority",
              "fix": "Describe each one: format, units, an example, and what happens when it's left out."
            },
            {
              "rule": "TC11",
              "severity": "warn",
              "tool": "compute_lrs_composite",
              "message": "none of its 4 parameters has a description",
              "fix": "Describe each one: format, units, an example, and what happens when it's left out."
            },
            {
              "rule": "TC11",
              "severity": "warn",
              "tool": "compute_lrs_composite_v2",
              "message": "7 parameters without a description: barrierScore, budgetProofScore, buildComplexityPenalty, monetizationScore, searchVelocityScore, socialPainScore and 1 more",
              "fix": "Describe each one: format, units, an example, and what happens when it's left out."
            },
            {
              "rule": "TC11",
              "severity": "warn",
              "tool": "compute_monetization",
              "message": "1 parameter without a description: pricingAnchorsCount",
              "fix": "Describe each one: format, units, an example, and what happens when it's left out."
            },
            {
              "rule": "TC11",
              "severity": "warn",
              "tool": "compute_multi_source_tam",
              "message": "3 parameters without a description: inputs, inputs[].source, inputs[].text",
              "fix": "Describe each one: format, units, an example, and what happens when it's left out."
            },
            {
              "rule": "TC11",
              "severity": "warn",
              "tool": "compute_ppc_spend_signal",
              "message": "none of its 4 parameters has a description",
              "fix": "Describe each one: format, units, an example, and what happens when it's left out."
            },
            {
              "rule": "TC11",
              "severity": "warn",
              "tool": "compute_search_velocity",
              "message": "2 parameters without a description: geoRegionCount, risingQueriesCount",
              "fix": "Describe each one: format, units, an example, and what happens when it's left out."
            },
            {
              "rule": "TC11",
              "severity": "warn",
              "tool": "compute_social_pain",
              "message": "none of its 4 parameters has a description",
              "fix": "Describe each one: format, units, an example, and what happens when it's left out."
            },
            {
              "rule": "TC11",
              "severity": "warn",
              "tool": "compute_urgency_composite",
              "message": "none of its 3 parameters has a description",
              "fix": "Describe each one: format, units, an example, and what happens when it's left out."
            },
            {
              "rule": "TC11",
              "severity": "warn",
              "tool": "compute_x_signal",
              "message": "none of its 5 parameters has a description",
              "fix": "Describe each one: format, units, an example, and what happens when it's left out."
            },
            {
              "rule": "TC11",
              "severity": "warn",
              "tool": "derive_kill_criteria",
              "message": "1 parameter without a description: icpDriftCount",
              "fix": "Describe each one: format, units, an example, and what happens when it's left out."
            },
            {
              "rule": "TC11",
              "severity": "warn",
              "tool": "validate_unit_economics",
              "message": "none of its 7 parameters has a description",
              "fix": "Describe each one: format, units, an example, and what happens when it's left out."
            },
            {
              "rule": "TC13",
              "severity": "warn",
              "tool": "compute_collection_scores",
              "message": "enrichedData (object with no properties)",
              "fix": "Declare the properties (or additionalProperties with a schema) and the array's items."
            },
            {
              "rule": "TC13",
              "severity": "warn",
              "tool": "derive_kill_criteria",
              "message": "dealbreakers (object with no properties), unitEcon (object with no properties)",
              "fix": "Declare the properties (or additionalProperties with a schema) and the array's items."
            },
            {
              "rule": "TC16",
              "severity": "warn",
              "tool": "compute_barrier",
              "message": "no readOnlyHint or destructiveHint",
              "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
            },
            {
              "rule": "TC16",
              "severity": "warn",
              "tool": "compute_budget_proof",
              "message": "no readOnlyHint or destructiveHint",
              "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
            },
            {
              "rule": "TC16",
              "severity": "warn",
              "tool": "compute_build_complexity",
              "message": "no readOnlyHint or destructiveHint",
              "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
            },
            {
              "rule": "TC16",
              "severity": "warn",
              "tool": "compute_collection_scores",
              "message": "no readOnlyHint or destructiveHint",
              "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
            },
            {
              "rule": "TC16",
              "severity": "warn",
              "tool": "compute_crossed_matrix",
              "message": "no readOnlyHint or destructiveHint",
              "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
            },
            {
              "rule": "TC16",
              "severity": "warn",
              "tool": "compute_dealbreakers_v2",
              "message": "no readOnlyHint or destructiveHint",
              "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
            },
            {
              "rule": "TC16",
              "severity": "warn",
              "tool": "compute_funding_momentum",
              "message": "no readOnlyHint or destructiveHint",
              "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
            },
            {
              "rule": "TC16",
              "severity": "warn",
              "tool": "compute_hiring_demand",
              "message": "no readOnlyHint or destructiveHint",
              "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
            },
            {
              "rule": "TC16",
              "severity": "warn",
              "tool": "compute_lrs_composite",
              "message": "no readOnlyHint or destructiveHint",
              "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
            },
            {
              "rule": "TC16",
              "severity": "warn",
              "tool": "compute_lrs_composite_v2",
              "message": "no readOnlyHint or destructiveHint",
              "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
            },
            {
              "rule": "TC16",
              "severity": "warn",
              "tool": "compute_monetization",
              "message": "no readOnlyHint or destructiveHint",
              "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
            },
            {
              "rule": "TC16",
              "severity": "warn",
              "tool": "compute_multi_source_tam",
              "message": "no readOnlyHint or destructiveHint",
              "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
            },
            {
              "rule": "TC16",
              "severity": "warn",
              "tool": "compute_ppc_spend_signal",
              "message": "no readOnlyHint or destructiveHint",
              "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
            },
            {
              "rule": "TC16",
              "severity": "warn",
              "tool": "compute_search_velocity",
              "message": "no readOnlyHint or destructiveHint",
              "fix": "Its name starts with \"search\"; if it only reads, set readOnlyHint: true so harnesses can run it without asking."
            },
            {
              "rule": "TC16",
              "severity": "warn",
              "tool": "compute_search_velocity_v2",
              "message": "no readOnlyHint or destructiveHint",
              "fix": "Its name starts with \"search\"; if it only reads, set readOnlyHint: true so harnesses can run it without asking."
            },
            {
              "rule": "TC16",
              "severity": "warn",
              "tool": "compute_social_pain",
              "message": "no readOnlyHint or destructiveHint",
              "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
            },
            {
              "rule": "TC16",
              "severity": "warn",
              "tool": "compute_urgency_composite",
              "message": "no readOnlyHint or destructiveHint",
              "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
            },
            {
              "rule": "TC16",
              "severity": "warn",
              "tool": "compute_x_signal",
              "message": "no readOnlyHint or destructiveHint",
              "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
            },
            {
              "rule": "TC16",
              "severity": "warn",
              "tool": "derive_kill_criteria",
              "message": "no readOnlyHint or destructiveHint",
              "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
            },
            {
              "rule": "TC16",
              "severity": "warn",
              "tool": "get_started",
              "message": "no readOnlyHint or destructiveHint",
              "fix": "Its name starts with \"get\"; if it only reads, set readOnlyHint: true so harnesses can run it without asking."
            },
            {
              "rule": "TC16",
              "severity": "warn",
              "tool": "validate_unit_economics",
              "message": "no readOnlyHint or destructiveHint",
              "fix": "Its name starts with \"validate\"; if it only reads, set readOnlyHint: true so harnesses can run it without asking."
            },
            {
              "rule": "TC24",
              "severity": "note",
              "message": "21 of 21 tools have no outputSchema",
              "fix": "Declare outputSchema for tools that return structured data, and return structuredContent that matches it."
            }
          ]
        },
        "checkedAt": "2026-10-04T22:25:56Z",
        "count": 21,
        "schemaTokens": 4112,
        "status": "ok",
        "tools": [
          {
            "name": "get_started",
            "description": "What this server is, what it will do for you right now without an account, and what an account adds. Call this first if you have no API key — it answers in one round trip instead of sending you to a website.",
            "inputSchema": {
              "properties": {},
              "required": [],
              "type": "object"
            }
          },
          {
            "name": "compute_barrier",
            "description": "Compute barrier_score (0-24) + label (PRISTINE/OPEN/COMPETITIVE/CROWDED) from competitor counts + SERP noise fraction.",
            "inputSchema": {
              "properties": {
                "adjacentCompetitorCount": {
                  "default": 0,
                  "minimum": 0,
                  "type": "integer"
                },
                "directCompetitorCount": {
                  "minimum": 0,
                  "type": "integer"
                },
                "serpNoise": {
                  "default": 0,
                  "maximum": 1,
                  "minimum": 0,
                  "type": "number"
                }
              },
              "required": [
                "directCompetitorCount"
              ],
              "type": "object"
            }
          },
          {
            "name": "compute_budget_proof",
            "description": "Compute budget_proof_score (0-10) + label (STRONG/CONFIRMED/WEAK/ABSENT) + purchase_intent_pct from pricing hits + review-site hits + intent mentions.",
            "inputSchema": {
              "properties": {
                "hasNamedPricing": {
                  "type": "boolean"
                },
                "pricingHitsCount": {
                  "minimum": 0,
                  "type": "integer"
                },
                "purchaseIntentMentions": {
                  "minimum": 0,
                  "type": "integer"
                },
                "reviewSiteHitsCount": {
                  "minimum": 0,
                  "type": "integer"
                }
              },
              "required": [
                "pricingHitsCount"
              ],
              "type": "object"
            }
          },
          {
            "name": "compute_build_complexity",
            "description": "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.",
            "inputSchema": {
              "properties": {
                "externalApisCount": {
                  "minimum": 0,
                  "type": "integer"
                },
                "integrationsCount": {
                  "minimum": 0,
                  "type": "integer"
                },
                "stackComplexityTags": {
                  "items": {
                    "type": "string"
                  },
                  "type": "array"
                }
              },
              "required": [
                "externalApisCount"
              ],
              "type": "object"
            }
          },
          {
            "name": "compute_collection_scores",
            "description": "Compute 12 deterministic collection scores (0-100) + badges + death reason for an enriched idea. Pure math. No external calls.",
            "inputSchema": {
              "properties": {
                "analysisId": {
                  "type": "string"
                },
                "enrichedData": {
                  "description": "EnrichedData with canonical_idea signals.",
                  "type": "object"
                }
              },
              "required": [
                "analysisId",
                "enrichedData"
              ],
              "type": "object"
            }
          },
          {
            "name": "compute_crossed_matrix",
            "description": "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.",
            "inputSchema": {
              "properties": {
                "hasMajorContradiction": {
                  "default": false,
                  "type": "boolean"
                },
                "lensScores": {
                  "items": {
                    "properties": {
                      "confidence": {
                        "maximum": 1,
                        "minimum": 0,
                        "type": "number"
                      },
                      "lens": {
                        "enum": [
                          "team",
                          "problem_solution",
                          "traction",
                          "competition",
                          "gtm",
                          "finance"
                        ],
                        "type": "string"
                      },
                      "redFlag": {
                        "type": "boolean"
                      },
                      "score": {
                        "maximum": 100,
                        "minimum": 0,
                        "type": "number"
                      }
                    },
                    "required": [
                      "lens",
                      "score",
                      "confidence"
                    ],
                    "type": "object"
                  },
                  "type": "array"
                },
                "observer": {
                  "description": "Founder profile that crosses with the substrate idea to produce an observer-relative verdict. When omitted, only the substrate verdict is returned.",
                  "properties": {
                    "capital_usd_band": {
                      "enum": [
                        "under_50k",
                        "50k_500k",
                        "500k_5m",
                        "over_5m"
                      ],
                      "type": "string"
                    },
                    "exit_goal": {
                      "enum": [
                        "lifestyle",
                        "acquisition",
                        "ipo",
                        "unicorn"
                      ],
                      "type": "string"
                    },
                    "expertise_sectors": {
                      "items": {
                        "maxLength": 80,
                        "minLength": 2,
                        "type": "string"
                      },
                      "maxItems": 8,
                      "type": "array"
                    },
                    "founder_type": {
                      "enum": [
                        "solo",
                        "cofounded_technical",
                        "cofounded_business",
                        "domain_expert",
                        "serial"
                      ],
                      "type": "string"
                    },
                    "risk_tolerance": {
                      "enum": [
                        "conservative",
                        "moderate",
                        "aggressive"
                      ],
                      "type": "string"
                    },
                    "runway_months": {
                      "maximum": 60,
                      "minimum": 0,
                      "type": "integer"
                    },
                    "time_horizon_years": {
                      "maximum": 15,
                      "minimum": 1,
                      "type": "integer"
                    }
                  },
                  "required": [
                    "founder_type"
                  ],
                  "type": "object"
                },
                "sector": {
                  "type": "string"
                },
                "stage": {
                  "enum": [
                    "idea",
                    "mvp",
                    "seed",
                    "series_a_plus"
                  ],
                  "type": "string"
                },
                "stageProbabilities": {
                  "properties": {
                    "idea": {
                      "maximum": 1,
                      "minimum": 0,
                      "type": "number"
                    },
                    "mvp": {
                      "maximum": 1,
                      "minimum": 0,
                      "type": "number"
                    },
                    "seed": {
                      "maximum": 1,
                      "minimum": 0,
                      "type": "number"
                    },
                    "series_a_plus": {
                      "maximum": 1,
                      "minimum": 0,
                      "type": "number"
                    }
                  },
                  "type": "object"
                },
                "unresolvedContradictions": {
                  "default": 0,
                  "minimum": 0,
                  "type": "integer"
                }
              },
              "required": [
                "stage",
                "lensScores"
              ],
              "type": "object"
            }
          },
          {
            "name": "compute_dealbreakers_v2",
            "description": "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\u003c50) is observer-invariant — fatal stays fatal.",
            "inputSchema": {
              "properties": {
                "hasMajorContradiction": {
                  "default": false,
                  "type": "boolean"
                },
                "lensScores": {
                  "items": {
                    "properties": {
                      "confidence": {
                        "maximum": 1,
                        "minimum": 0,
                        "type": "number"
                      },
                      "lens": {
                        "enum": [
                          "team",
                          "problem_solution",
                          "traction",
                          "competition",
                          "gtm",
                          "finance"
                        ],
                        "type": "string"
                      },
                      "redFlag": {
                        "type": "boolean"
                      },
                      "score": {
                        "maximum": 100,
                        "minimum": 0,
                        "type": "number"
                      }
                    },
                    "required": [
                      "lens",
                      "score",
                      "confidence"
                    ],
                    "type": "object"
                  },
                  "type": "array"
                },
                "observer": {
                  "description": "Founder profile that crosses with the substrate idea to produce an observer-relative verdict. When omitted, only the substrate verdict is returned.",
                  "properties": {
                    "capital_usd_band": {
                      "enum": [
                        "under_50k",
                        "50k_500k",
                        "500k_5m",
                        "over_5m"
                      ],
                      "type": "string"
                    },
                    "exit_goal": {
                      "enum": [
                        "lifestyle",
                        "acquisition",
                        "ipo",
                        "unicorn"
                      ],
                      "type": "string"
                    },
                    "expertise_sectors": {
                      "items": {
                        "maxLength": 80,
                        "minLength": 2,
                        "type": "string"
                      },
                      "maxItems": 8,
                      "type": "array"
                    },
                    "founder_type": {
                      "enum": [
                        "solo",
                        "cofounded_technical",
                        "cofounded_business",
                        "domain_expert",
                        "serial"
                      ],
                      "type": "string"
                    },
                    "risk_tolerance": {
                      "enum": [
                        "conservative",
                        "moderate",
                        "aggressive"
                      ],
                      "type": "string"
                    },
                    "runway_months": {
                      "maximum": 60,
                      "minimum": 0,
                      "type": "integer"
                    },
                    "time_horizon_years": {
                      "maximum": 15,
                      "minimum": 1,
                      "type": "integer"
                    }
                  },
                  "required": [
                    "founder_type"
                  ],
                  "type": "object"
                },
                "sector": {
                  "type": "string"
                },
                "stage": {
                  "enum": [
                    "idea",
                    "mvp",
                    "seed",
                    "series_a_plus"
                  ],
                  "type": "string"
                },
                "stageProbabilities": {
                  "properties": {
                    "idea": {
                      "maximum": 1,
                      "minimum": 0,
                      "type": "number"
                    },
                    "mvp": {
                      "maximum": 1,
                      "minimum": 0,
                      "type": "number"
                    },
                    "seed": {
                      "maximum": 1,
                      "minimum": 0,
                      "type": "number"
                    },
                    "series_a_plus": {
                      "maximum": 1,
                      "minimum": 0,
                      "type": "number"
                    }
                  },
                  "type": "object"
                },
                "unresolvedContradictions": {
                  "default": 0,
                  "minimum": 0,
                  "type": "integer"
                }
              },
              "required": [
                "stage",
                "lensScores"
              ],
              "type": "object"
            }
          },
          {
            "name": "compute_funding_momentum",
            "description": "Compute funding_momentum_score (0-10) + badge (HOT/WARM/COOL/COLD) from tier-weighted funding-article hit counts.",
            "inputSchema": {
              "properties": {
                "hitsByTier": {
                  "properties": {
                    "presswire": {
                      "minimum": 0,
                      "type": "integer"
                    },
                    "regional": {
                      "minimum": 0,
                      "type": "integer"
                    },
                    "tier_1": {
                      "minimum": 0,
                      "type": "integer"
                    },
                    "vertical": {
                      "minimum": 0,
                      "type": "integer"
                    }
                  },
                  "type": "object"
                },
                "recent30dHits": {
                  "minimum": 0,
                  "type": "integer"
                }
              },
              "required": [
                "hitsByTier"
              ],
              "type": "object"
            }
          },
          {
            "name": "compute_hiring_demand",
            "description": "Compute hiring_demand_score (0-10) from priority-weighted ATS site hit counts (use registries/hiring-sources for priorities).",
            "inputSchema": {
              "properties": {
                "sites": {
                  "items": {
                    "properties": {
                      "domain": {
                        "type": "string"
                      },
                      "hits": {
                        "minimum": 0,
                        "type": "integer"
                      },
                      "priority": {
                        "enum": [
                          1,
                          2,
                          3
                        ],
                        "type": "integer"
                      }
                    },
                    "required": [
                      "domain",
                      "hits",
                      "priority"
                    ],
                    "type": "object"
                  },
                  "type": "array"
                }
              },
              "required": [
                "sites"
              ],
              "type": "object"
            }
          },
          {
            "name": "compute_lrs_composite_v2",
            "description": "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 (\u003c40).",
            "inputSchema": {
              "properties": {
                "barrierScore": {
                  "maximum": 24,
                  "minimum": 0,
                  "type": "number"
                },
                "budgetProofScore": {
                  "maximum": 10,
                  "minimum": 0,
                  "type": "number"
                },
                "buildComplexityPenalty": {
                  "maximum": 10,
                  "minimum": 0,
                  "type": "number"
                },
                "monetizationScore": {
                  "maximum": 21,
                  "minimum": 0,
                  "type": "number"
                },
                "searchVelocityScore": {
                  "maximum": 25,
                  "minimum": 0,
                  "type": "number"
                },
                "sectorProfile": {
                  "description": "Opt-in sector weight override. Default uses Python canonical weights.",
                  "enum": [
                    "default",
                    "ai_native",
                    "creator",
                    "crypto"
                  ],
                  "type": "string"
                },
                "socialPainScore": {
                  "maximum": 30,
                  "minimum": 0,
                  "type": "number"
                },
                "xSignalScore": {
                  "maximum": 20,
                  "minimum": 0,
                  "type": "number"
                }
              },
              "required": [
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                "socialPainScore",
                "barrierScore",
                "monetizationScore",
                "xSignalScore",
                "budgetProofScore"
              ],
              "type": "object"
            }
          },
          {
            "name": "compute_lrs_composite",
            "description": "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.",
            "inputSchema": {
              "properties": {
                "barrierScore": {
                  "maximum": 24,
                  "minimum": 0,
                  "type": "number"
                },
                "monetizationScore": {
                  "maximum": 21,
                  "minimum": 0,
                  "type": "number"
                },
                "searchVelocityScore": {
                  "maximum": 25,
                  "minimum": 0,
                  "type": "number"
                },
                "socialPainScore": {
                  "maximum": 30,
                  "minimum": 0,
                  "type": "number"
                }
              },
              "required": [
                "searchVelocityScore",
                "socialPainScore",
                "barrierScore",
                "monetizationScore"
              ],
              "type": "object"
            }
          },
          {
            "name": "compute_monetization",
            "description": "Compute monetization_score (0-21) + label + has_pricing_anchors from pricing anchors + model tags + deal cycle hint.",
            "inputSchema": {
              "properties": {
                "dealCycle": {
                  "description": "instant/days/weeks/months/quarters",
                  "type": "string"
                },
                "modelTags": {
                  "description": "e.g. [\"subscription\",\"usage\",\"marketplace\"]",
                  "items": {
                    "type": "string"
                  },
                  "type": "array"
                },
                "pricingAnchorsCount": {
                  "minimum": 0,
                  "type": "integer"
                }
              },
              "required": [
                "pricingAnchorsCount"
              ],
              "type": "object"
            }
          },
          {
            "name": "compute_multi_source_tam",
            "description": "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.",
            "inputSchema": {
              "properties": {
                "inputs": {
                  "items": {
                    "properties": {
                      "estimateYear": {
                        "description": "Optional: year the estimate was published.",
                        "maximum": 2100,
                        "minimum": 1990,
                        "type": "integer"
                      },
                      "source": {
                        "type": "string"
                      },
                      "text": {
                        "type": "string"
                      }
                    },
                    "required": [
                      "source",
                      "text"
                    ],
                    "type": "object"
                  },
                  "type": "array"
                }
              },
              "required": [
                "inputs"
              ],
              "type": "object"
            }
          },
          {
            "name": "compute_ppc_spend_signal",
            "description": "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.",
            "inputSchema": {
              "properties": {
                "avgCpcUsd": {
                  "minimum": 0,
                  "type": "number"
                },
                "competition": {
                  "maximum": 1,
                  "minimum": 0,
                  "type": "number"
                },
                "competitorBidders": {
                  "minimum": 0,
                  "type": "integer"
                },
                "totalMonthlySpendUsd": {
                  "minimum": 0,
                  "type": "number"
                }
              },
              "required": [
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                "totalMonthlySpendUsd"
              ],
              "type": "object"
            }
          },
          {
            "name": "compute_search_velocity_v2",
            "description": "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\u003c50 zeroes the trend component (Yotpo SEO floor). Optional daysSinceLastSignal applies exponential freshness decay (search half-life 90d).",
            "inputSchema": {
              "properties": {
                "daysSinceLastSignal": {
                  "description": "Optional: days since most recent confirming signal. Triggers exponential freshness decay (half-life 90d).",
                  "minimum": 0,
                  "type": "number"
                },
                "externalVolumeNorm": {
                  "description": "Normalized 0-1 demand volume from EXTERNAL sources (Amazon, app stores, jobs). Caller normalizes before passing.",
                  "maximum": 1,
                  "minimum": 0,
                  "type": "number"
                },
                "geoSpreadNorm": {
                  "description": "0-1 geographic spread (regions with interest \u003e threshold).",
                  "maximum": 1,
                  "minimum": 0,
                  "type": "number"
                },
                "intentNorm": {
                  "description": "0-1 commercial/transactional intent ratio.",
                  "maximum": 1,
                  "minimum": 0,
                  "type": "number"
                },
                "trendsTimelineValues": {
                  "description": "Monthly Trends values 0-100. Used ONLY to derive trendNorm — never as raw volume.",
                  "items": {
                    "maximum": 100,
                    "minimum": 0,
                    "type": "number"
                  },
                  "type": "array"
                }
              },
              "required": [
                "trendsTimelineValues",
                "externalVolumeNorm",
                "intentNorm",
                "geoSpreadNorm"
              ],
              "type": "object"
            }
          },
          {
            "name": "compute_search_velocity",
            "description": "Compute search_velocity_score (0-25) from Trends timeline values + rising queries count + geo region count.",
            "inputSchema": {
              "properties": {
                "geoRegionCount": {
                  "minimum": 0,
                  "type": "integer"
                },
                "risingQueriesCount": {
                  "minimum": 0,
                  "type": "integer"
                },
                "timelineValues": {
                  "description": "Monthly Trends values 0-100 (e.g. last 10-12 months).",
                  "items": {
                    "maximum": 100,
                    "minimum": 0,
                    "type": "number"
                  },
                  "type": "array"
                }
              },
              "required": [
                "timelineValues"
              ],
              "type": "object"
            }
          },
          {
            "name": "compute_social_pain",
            "description": "Compute social_pain_score (0-30) + total mentions + dominant perspective (business/consumer/trend/mixed).",
            "inputSchema": {
              "properties": {
                "categoryCounts": {
                  "properties": {
                    "business": {
                      "minimum": 0,
                      "type": "integer"
                    },
                    "consumer": {
                      "minimum": 0,
                      "type": "integer"
                    },
                    "trend": {
                      "minimum": 0,
                      "type": "integer"
                    }
                  },
                  "type": "object"
                },
                "intentMentions": {
                  "default": 0,
                  "minimum": 0,
                  "type": "integer"
                },
                "painMentions": {
                  "minimum": 0,
                  "type": "integer"
                },
                "urgencyMentions": {
                  "default": 0,
                  "minimum": 0,
                  "type": "integer"
                }
              },
              "required": [
                "painMentions"
              ],
              "type": "object"
            }
          },
          {
            "name": "compute_urgency_composite",
            "description": "Compose composite_urgency_score (0-10) + badge (LOW/MEDIUM/HIGH/VERY_HIGH/EXTREME) from 3 sub-scores: news, pain, hiring.",
            "inputSchema": {
              "properties": {
                "hiringSignalScore": {
                  "maximum": 10,
                  "minimum": 0,
                  "type": "number"
                },
                "newsSignalScore": {
                  "maximum": 10,
                  "minimum": 0,
                  "type": "number"
                },
                "painSignalScore": {
                  "maximum": 10,
                  "minimum": 0,
                  "type": "number"
                }
              },
              "required": [
                "newsSignalScore",
                "painSignalScore",
                "hiringSignalScore"
              ],
              "type": "object"
            }
          },
          {
            "name": "compute_x_signal",
            "description": "Compute x_signal_score (0-20) + recency share + positivity rate from X/Twitter mention counts.",
            "inputSchema": {
              "properties": {
                "founderMentions": {
                  "minimum": 0,
                  "type": "integer"
                },
                "mentionsCount": {
                  "minimum": 0,
                  "type": "integer"
                },
                "recent7dCount": {
                  "minimum": 0,
                  "type": "integer"
                },
                "sentimentNegative": {
                  "minimum": 0,
                  "type": "integer"
                },
                "sentimentPositive": {
                  "minimum": 0,
                  "type": "integer"
                }
              },
              "required": [
                "mentionsCount"
              ],
              "type": "object"
            }
          },
          {
            "name": "derive_kill_criteria",
            "description": "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.",
            "inputSchema": {
              "properties": {
                "dealbreakers": {
                  "description": "The result of compute_dealbreakers_v2.",
                  "type": "object"
                },
                "icpDriftCount": {
                  "minimum": 0,
                  "type": "integer"
                },
                "unitEcon": {
                  "description": "The result of validate_unit_economics.",
                  "type": "object"
                }
              },
              "required": [],
              "type": "object"
            }
          },
          {
            "name": "validate_unit_economics",
            "description": "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.",
            "inputSchema": {
              "properties": {
                "annualRevenue": {
                  "type": "number"
                },
                "arpu": {
                  "type": "number"
                },
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                  "type": "number"
                },
                "customers": {
                  "type": "number"
                },
                "grossMargin": {
                  "type": "number"
                },
                "ltv": {
                  "type": "number"
                },
                "monthlyChurn": {
                  "type": "number"
                }
              },
              "required": [
                "customers",
                "arpu",
                "annualRevenue"
              ],
              "type": "object"
            }
          }
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  "markdown": "# ideaudit\n\n\u003e Indexed, not reviewed: facts from the official MCP registry and our own checks. No score, grade or rank, and not in the rankings until the panel reviews it. How the index works: https://www.anchorterminal.com/indexed/\n\n- Kind: MCP server, by inite.studio (https://inite.studio)\n- Listed because: It's published in the registry under inite.studio, a namespace the registry only gives to whoever proves they control that domain.\n- What the official MCP registry says: The scoring behind an audit allowed to say no. Twenty deterministic tools, offline, no account.\n\n## Facts\n\n- MCP registry: `studio.inite/ideaudit-tools` 1.1.0\n- Endpoint: https://api.inite.studio/mcp (streamable HTTP)\n- Package: npm `@inite/ideaudit-tools` (stdio)\n- Source: https://github.com/inite-ai/ideaudit-mcp\n- Website: https://inite.studio\n- npm downloads a week: 35\n- GitHub stars: 0\n- Registry entry updated: 2026-09-07\n\n## Tools\n\n- Tools it lists (21, about 4,112 tokens of context, `tools/list` without credentials over MCP 2025-11-25, checked 2026-10-04 22:25 UTC):\n  - `get_started`: What this server is, what it will do for you right now without an account, and what an account adds. Call this first if you have no API key — it answers in one…\n  - `compute_barrier`: Compute barrier_score (0-24) + label (PRISTINE/OPEN/COMPETITIVE/CROWDED) from competitor counts + SERP noise fraction.\n  - `compute_budget_proof`: Compute budget_proof_score (0-10) + label (STRONG/CONFIRMED/WEAK/ABSENT) + purchase_intent_pct from pricing hits + review-site hits + intent mentions.\n  - `compute_build_complexity`: Compute build_complexity_penalty (0-10, higher = worse) + per-factor breakdown. Hard tags:…\n  - `compute_collection_scores`: Compute 12 deterministic collection scores (0-100) + badges + death reason for an enriched idea. Pure math. No external calls.\n  - `compute_crossed_matrix`: Crossed-product audit explorer. Same input as compute_dealbreakers_v2 — returns substrate verdict (no-observer baseline) + crossed verdict (when observer…\n  - `compute_dealbreakers_v2`: Methodology v2 dealbreakers — stage-aware weights + confidence-weighted lens scoring + risk-asymmetric verdict (GO requires score≥80 AND zero red flags AND avg…\n  - `compute_funding_momentum`: Compute funding_momentum_score (0-10) + badge (HOT/WARM/COOL/COLD) from tier-weighted funding-article hit counts.\n  - `compute_hiring_demand`: Compute hiring_demand_score (0-10) from priority-weighted ATS site hit counts (use registries/hiring-sources for priorities).\n  - `compute_lrs_composite_v2`: 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…\n  - `compute_lrs_composite`: 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…\n  - `compute_monetization`: Compute monetization_score (0-21) + label + has_pricing_anchors from pricing anchors + model tags + deal cycle hint.\n  - `compute_multi_source_tam`: Multi-source TAM consensus. Pass 2-3 sources of market-size text. Optional `estimateYear` per source — when supplied, the result includes yearRange and a…\n  - `compute_ppc_spend_signal`: Wave 5 N.4 — compute ppc_spend_score (0-10) + label (STRONG/CONFIRMED/WEAK/ABSENT) + market_saturation from PPC traffic projection (avgCpcUsd,…\n  - `compute_search_velocity_v2`: 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…\n  - `compute_search_velocity`: Compute search_velocity_score (0-25) from Trends timeline values + rising queries count + geo region count.\n  - `compute_social_pain`: Compute social_pain_score (0-30) + total mentions + dominant perspective (business/consumer/trend/mixed).\n  - `compute_urgency_composite`: Compose composite_urgency_score (0-10) + badge (LOW/MEDIUM/HIGH/VERY_HIGH/EXTREME) from 3 sub-scores: news, pain, hiring.\n  - `compute_x_signal`: Compute x_signal_score (0-20) + recency share + positivity rate from X/Twitter mention counts.\n  - `derive_kill_criteria`: 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…\n  - `validate_unit_economics`: Sanity-check a unit-economics row before publishing it in a business-model slide. Catches the math-drift class of failures (customers × ARPU ≠ revenue),…\n- How its tools read to an agent (0 errors, 42 warnings, 1 note, about 4,112 tokens; rules at https://www.anchorterminal.com/check.md; not part of the score):\n  - warn TC11 compute_barrier: none of its 3 parameters has a description\n  - warn TC11 compute_budget_proof: none of its 4 parameters has a description\n  - warn TC11 compute_build_complexity: none of its 3 parameters has a description\n  - warn TC11 compute_collection_scores: 1 parameter without a description: analysisId\n  - warn TC11 compute_crossed_matrix: none of its 7 parameters has a description\n  - warn TC11 compute_dealbreakers_v2: none of its 7 parameters has a description\n  - warn TC11 compute_funding_momentum: none of its 2 parameters has a description\n  - warn TC11 compute_hiring_demand: 4 parameters without a description: sites, sites[].domain, sites[].hits, sites[].priority\n  - warn TC11 compute_lrs_composite: none of its 4 parameters has a description\n  - warn TC11 compute_lrs_composite_v2: 7 parameters without a description: barrierScore, budgetProofScore, buildComplexityPenalty, monetizationScore, searchVelocityScore, socialPainScore and 1 more\n  - warn TC11 compute_monetization: 1 parameter without a description: pricingAnchorsCount\n  - warn TC11 compute_multi_source_tam: 3 parameters without a description: inputs, inputs[].source, inputs[].text\n  - warn TC11 compute_ppc_spend_signal: none of its 4 parameters has a description\n  - warn TC11 compute_search_velocity: 2 parameters without a description: geoRegionCount, risingQueriesCount\n  - warn TC11 compute_social_pain: none of its 4 parameters has a description\n  - warn TC11 compute_urgency_composite: none of its 3 parameters has a description\n  - warn TC11 compute_x_signal: none of its 5 parameters has a description\n  - warn TC11 derive_kill_criteria: 1 parameter without a description: icpDriftCount\n  - warn TC11 validate_unit_economics: none of its 7 parameters has a description\n  - warn TC13 compute_collection_scores: enrichedData (object with no properties)\n  - warn TC13 derive_kill_criteria: dealbreakers (object with no properties), unitEcon (object with no properties)\n  - warn TC16 compute_barrier: no readOnlyHint or destructiveHint\n  - warn TC16 compute_budget_proof: no readOnlyHint or destructiveHint\n  - warn TC16 compute_build_complexity: no readOnlyHint or destructiveHint\n\n- JSON: https://www.anchorterminal.com/api/v1/tools/inite-ideaudit-tools.json\n- Being indexed says nothing about quality, and nobody can pay for it. Ask for a review: https://www.anchorterminal.com/builders/#claiming\n",
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