{"uid":"cap_qgC6mBq51pIH-_EvHsojy","slug":"us-brand-signal-policy-simulator-5380f07f","name":"US Brand Signal Policy Simulator","description":"Pay-per-call data & tool APIs","url":"https://api.timzinin.com/api/us-brand-signal-policy-simulator","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["signalId","normalizedScore"],"properties":{"signalId":{"type":"string","pattern":"^[A-Za-z0-9][A-Za-z0-9._:-]{0,63}$","maxLength":64,"minLength":1},"normalizedScore":{"type":"integer","maximum":100,"minimum":1}},"additionalProperties":false},"maxItems":100,"minItems":1},"policies":{"type":"array","items":{"type":"object","required":["policyId","reviewThreshold","acceptThreshold","thresholdOrder"],"properties":{"policyId":{"type":"string","pattern":"^[A-Za-z0-9][A-Za-z0-9._:-]{0,63}$","maxLength":64,"minLength":1},"thresholdOrder":{"enum":["review_lt_accept"],"type":"string"},"acceptThreshold":{"type":"integer","maximum":100,"minimum":1},"reviewThreshold":{"type":"integer","maximum":100,"minimum":1}},"additionalProperties":false},"maxItems":20,"minItems":1},"schemaVersion":{"enum":["1.0"],"type":"string"}}},"responseSchema":{"type":"json","example":{"meta":{"run_ms":1200,"settled":true,"item_count":1},"results":[{"counts":{"rows":4,"policies":3,"comparisons":3,"sensitivityRows":4},"totalRows":4,"reportType":"us_brand_signal_policy_simulator","rowsDigest":"911caadd6dc1c410ed601d2b580171dbb229935e8832de4b6a72a6747fcac4a5","attribution":{"type":"buyer_supplied_scores_and_policies","meaning":"Rows and thresholds were supplied by the buyer; this Actor simulates the stated policies only and makes no truth claim, recommendation, or winner selection."},"comparisons":[{"policyA":"balanced","policyB":"broad","reviewOnlyInA":0,"reviewOnlyInB":1,"acceptedOnlyInA":0,"acceptedOnlyInB":0,"rejectedOnlyInA":1,"rejectedOnlyInB":0,"sameDecisionCount":3,"changedSignalCount":1},{"policyA":"balanced","policyB":"strict","reviewOnlyInA":1,"reviewOnlyInB":1,"acceptedOnlyInA":1,"acceptedOnlyInB":0,"rejectedOnlyInA":0,"rejectedOnlyInB":1,"sameDecisionCount":2,"changedSignalCount":2},{"policyA":"broad","policyB":"strict","reviewOnlyInA":2,"reviewOnlyInB":1,"acceptedOnlyInA":1,"acceptedOnlyInB":0,"rejectedOnlyInA":0,"rejectedOnlyInB":2,"sameDecisionCount":1,"changedSignalCount":3}],"inputDigest":"cb1a39d72bddee8ad1a44f025db9f4a6a1f513ea6a86d094f1d0fe483444d291","resultDigest":"1be9ae6e4daebcd67c8960b9aa6f2bbd14d6121f497d7f7635d120d2fe97a493","policyResults":[{"counts":{"total":4,"review":1,"accepted":2,"rejected":1},"policyId":"balanced","reviewIds":["signal-003"],"acceptedIds":["signal-001","signal-002"],"rejectedIds":["signal-004"],"acceptThreshold":80,"reviewThreshold":50,"classificationDigest":"f40bc496a84f4d6504946cdaa8825468a26066d320a1fc6fed3fdbe3b1dbc0ff"},{"counts":{"total":4,"review":2,"accepted":2,"rejected":0},"policyId":"broad","reviewIds":["signal-003","signal-004"],"acceptedIds":["signal-001","signal-002"],"rejectedIds":[],"acceptThreshold":70,"reviewThreshold":30,"classificationDigest":"84aa5bc4a72f7a5e0517a46eb9873a9f86d5aa4a5fd8a56a60dd7657a5717be5"},{"counts":{"total":4,"review":1,"accepted":1,"rejected":2},"policyId":"strict","reviewIds":["signal-002"],"acceptedIds":["signal-001"],"rejectedIds":["signal-003","signal-004"],"acceptThreshold":90,"reviewThreshold":70,"classificationDigest":"7af0d1e326b8c9fae5ab550d3d8d25cda1b83bc51c5e2ea81ae2d45b054312a5"}],"schemaVersion":"1.0","totalPolicies":3,"policiesDigest":"ab9be549456b60293338f5088097494f3481886c57e6490058b49a070df01156","comparisonsDigest":"c8bc231bd36307ed00b100f7dfc77d9b0f8f6a2df72b062915fc9f6816db160f","sensitivityDigest":"20936e7f4ab8fabdd4af527ca46c766b60ad94576ee583874bd1e2aac1decce1","sensitivitySummary":[{"signalId":"signal-001","decisionSpread":1,"reviewByPolicyCount":0,"acceptedByPolicyCount":3,"rejectedByPolicyCount":0},{"signalId":"signal-002","decisionSpread":2,"reviewByPolicyCount":1,"acceptedByPolicyCount":2,"rejectedByPolicyCount":0},{"signalId":"signal-003","decisionSpread":2,"reviewByPolicyCount":2,"acceptedByPolicyCount":0,"rejectedByPolicyCount":1},{"signalId":"signal-004","decisionSpread":2,"reviewByPolicyCount":1,"acceptedByPolicyCount":0,"rejectedByPolicyCount":2}],"policyResultsDigest":"e4a33873c0ca737d4e419ab0e22c0e954d1742922fe965ab6e709d52a14b1523"}]}},"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.05","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.05/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.05","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.05","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_Sd1_VSQr1wfQOAaOWlviP","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.05","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Simulates and compares multiple brand-safety scoring policies against buyer-supplied signal scores, returning accept/review/reject classifications and cross-policy divergence counts for US brand signals.","exampleAgentPrompt":"Simulate three brand signal policies — balanced (accept at 80, review at 50), broad (accept at 70, review at 30), and strict (accept at 90, review at 60) — against my 4 scored US brand signals (signal-001: 92, signal-002: 85, signal-003: 55, signal-004: 35) and show me how many signals each policy accepts, rejects, or routes to review, plus where they disagree with each other.","exampleUseCases":[{"title":"Pre-launch policy threshold calibration","prompt":"I have 6 US brand signals scored between 20 and 95. Run them through two policies — a conservative one (accept at 85, review at 60) and a permissive one (accept at 65, review at 25) — and tell me how many signals end up in each bucket and where the two policies disagree."},{"title":"Auditing divergence between brand review teams","prompt":"My brand safety team uses a balanced policy (accept at 80, review at 50) but a partner wants to use a broad policy (accept at 70, review at 30). Simulate both against these 5 brand signal scores and show me exactly which signals get classified differently between the two approaches."},{"title":"Stress-testing strict brand acceptance criteria","prompt":"Run a policy simulation on 8 US brand signals with a strict policy (accept at 90, review at 70) and a standard policy (accept at 75, review at 45) — I want to see how many signals we'd lose from accepted to rejected if we tighten our thresholds."}],"resultDescription":"Returns a JSON object with per-policy classification counts (accepted, reviewed, rejected) and IDs, pairwise cross-policy comparison metrics (changed signal count, decisions only in A vs B), row/input/result digests for auditability, and an attribution note clarifying the simulation makes no winner recommendation.","failureModes":["Invalid or missing signal scores cause validation error","Threshold values out of range (e.g. accept threshold below review threshold) may return an error","Malformed policy definitions cause a 400-level response","Empty signal list returns zero-count results with valid structure","Network timeout on heavy input sets (run_ms may exceed SLA)"],"whenToPreferThis":"Use this endpoint when you need to compare the downstream effects of different brand-safety threshold policies on a known set of scored signals before committing to a policy in production. It is ideal for buyers who already have their own scored signals and want to stress-test or audit policy choices without any external truth-claim or recommendation — the simulator is purely deterministic against buyer-supplied inputs.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-09-14T18:49:25.200Z","isFirstParty":false}