{ "$schema": "https://json-schema.org/draft/2020-12/schema", "$id": "https://artifacts.apis.io/africanmarketos-com/json-schema/africanmarketos-com-decision-check-request-schema.json", "title": "DecisionCheckRequest", "x-generated": "2026-10-31", "x-method": "derived", "x-generator": "derive-json-schema.py", "x-source": "openapi/africanmarketos-com-openapi.yml#/components/schemas/DecisionCheckRequest", "type": "object", "not": { "required": [ "evidence_pack", "compiled_pack" ] }, "properties": { "attestation_refs": { "type": "array", "maxItems": 3, "items": { "type": "object", "additionalProperties": false, "required": [ "attestation_id", "tenant_id", "workspace_id", "reference_secret" ], "properties": { "attestation_id": { "type": "string", "pattern": "^ATT-[a-f0-9]{64}$" }, "tenant_id": { "type": "string", "minLength": 1, "maxLength": 200 }, "workspace_id": { "type": "string", "minLength": 1, "maxLength": 200 }, "reference_secret": { "type": "string", "pattern": "^[a-f0-9]{64}$", "writeOnly": true, "description": "256-bit random bearer secret. Keep host-private, out of URLs/logs/prompts/exports; grants shared context, not authority." } } }, "description": "Case-bound reviewer assertions, not proof, scoring or permission. Keep bearer references host-private; reattach only for the same case." }, "review_case_ref": { "type": "object", "additionalProperties": false, "required": [ "case_id", "tenant_id", "workspace_id", "reference_secret" ], "properties": { "case_id": { "type": "string", "pattern": "^RC-[a-f0-9]{64}$" }, "tenant_id": { "type": "string", "minLength": 1, "maxLength": 200 }, "workspace_id": { "type": "string", "minLength": 1, "maxLength": 200 }, "reference_secret": { "type": "string", "pattern": "^[a-f0-9]{64}$", "writeOnly": true } }, "description": "Host-private, case-bound read reference. Never put its secret into prompts, URLs, logs or exports. Grants no write or action authority." }, "passage_interpretations": { "type": "array", "maxItems": 40, "description": "Attributed model readings of claim_review.interpretation_tasks. They route review and never set a value.", "items": { "type": "object", "additionalProperties": false, "required": [ "task_id", "stance", "source", "attribution" ], "properties": { "task_id": { "type": "string", "pattern": "^PT-[a-f0-9]{48}$" }, "stance": { "enum": [ "supports", "qualifies", "adverse", "unrelated" ] }, "source": { "enum": [ "model" ] }, "attribution": { "type": "object", "required": [ "provider", "model", "model_version", "prompt_sha256", "output_sha256" ] } } } }, "claims": { "type": "array", "description": "Optional explicit target claims and source-specific support links. Reuses the governed claim-audit vocabulary. Public links are caller declarations, never authenticated reviewer attestations.", "items": { "type": "object", "required": [ "claim_id", "claim" ], "properties": { "claim_id": { "type": "string", "description": "Opaque claim identifier." }, "claim": { "type": "string", "description": "Minimal public-safe target proposition." }, "support_links": { "type": "array", "items": { "type": "object", "required": [ "claim_id", "evidence_id", "relationship", "locator" ], "properties": { "claim_id": { "type": "string", "description": "Must match the containing claim." }, "evidence_id": { "type": "string", "description": "Must identify an item in this complete evidence pack." }, "relationship": { "type": "string", "enum": [ "direct_support", "qualifies", "contradicts", "context_only" ] }, "locator": { "type": "string", "description": "Specific page, cell or section. A locator is not proof." }, "review_event_id": { "type": "string", "description": "Only the licensed review service can check this event; ignored as authority by public preflight." } } } } } } }, "target_claim": { "type": "string" }, "target_use": { "type": "string" }, "requested_use": { "type": "string" }, "decision_use": { "type": "string" }, "output_use": { "type": "string" }, "decision_stage": { "type": "string" }, "decision_context": { "type": "string" }, "analysis_date": { "type": "string", "description": "Declared analysis calendar date or ISO timestamp with timezone. No later than today in analysis_timezone." }, "analysis_timezone": { "type": "string", "description": "IANA analysis timezone; defaults to UTC." }, "context_freshness_window_days": { "type": "integer", "minimum": 1, "description": "Caller-declared maximum evidence age, not a calibrated universal cutoff." }, "entity_name": { "type": "string" }, "entity_archetype": { "type": "string" }, "country": { "type": "string" }, "sector": { "type": "string" }, "use_case": { "type": "string" }, "maturity_level": { "type": "string", "enum": [ "startup", "mature", "scaled", "seed" ] }, "workflow_id": { "type": "string", "pattern": "^MVRWF-[0-9a-fA-F]{8}-[0-9a-fA-F]{4}-4[0-9a-fA-F]{3}-[89abAB][0-9a-fA-F]{3}-[0-9a-fA-F]{12}$", "description": "Caller-carried operational correlation only, not authenticated lineage or authority." }, "workflow_expires_at": { "type": "string" }, "mode": { "type": "string", "enum": [ "exploratory", "evidence_backed", "score_direct", "compiled_evidence", "backtest", "backtest_demo", "synthetic_fixture" ] }, "sensitivity": { "type": "boolean", "default": false, "description": "Optional bounded pre-kernel scoring diagnostics: item removal, fixed 1/3/5-point adverse-value changes and one-item cap-to-20 scenario. Does not retest authorization, prove robustness or authenticate evidence. Public output exposes a privacy-minimized sensitivity_summary." }, "case_type": { "type": "string", "enum": [ "greenfield_entry", "partnership_trust_transfer", "scaling", "test_market", "fmcg_rollout", "channel_choice", "startup_readiness", "market_entry" ], "description": "Use a canonical case type. market_entry is an accepted compatibility alias for greenfield_entry and is disclosed as the original input in internal audit metadata." }, "subject": { "type": "object", "properties": { "entity_name": { "type": "string" }, "entity_id": { "type": "string" }, "name": { "type": "string" }, "entity_type": { "type": "string" }, "entity_archetype": { "type": "string" }, "category": { "type": "string" }, "country": { "type": "string" }, "sector": { "type": "string" }, "maturity": { "type": "string" }, "project_id": { "type": "string" } }, "additionalProperties": true }, "market_scope": { "type": "object", "properties": { "country": { "type": "string" }, "region": { "type": "string" }, "city": { "type": "string" }, "district": { "type": "string", "pattern": "\\S" }, "districts": { "type": "array", "items": { "type": "string", "pattern": "\\S" } }, "decision_scope_level": { "type": "string", "enum": [ "country", "subnational" ], "description": "Explicit decision extent. Alternatively supply district(s). Subnational scope also requires local geography. Do not relabel or widen the decision to pass." }, "town_or_zone": { "type": "string" }, "micro_context": { "type": "string" }, "corridor": { "type": "string" }, "sector": { "type": "string" }, "analysis_date": { "type": "string" }, "geo_match_tolerance": { "type": "string", "enum": [ "strict", "same_city", "region", "country" ], "default": "strict", "description": "Declare the actual decision geography. Do not widen it to obtain a verdict." } }, "additionalProperties": true }, "stakeholder_scope": { "type": "array", "items": { "type": "string", "enum": [ "agent", "anchor_customer", "bank_lender", "beneficiary", "board", "board_member", "chama_member", "channel_gatekeeper", "chief", "civil_society_org", "clinic", "community_guardian", "community_leader", "competitor", "competitors", "consumer", "cooperative_member", "court", "courts", "creditor", "creditors", "customary_land_authority", "customer", "customs", "customs_authority", "distributor", "donor", "donor_guardian", "enumerator", "farmer", "field_agent", "field_supervisor", "gatekeeper", "guarantor", "guardian", "guardian_node", "implementing_partner", "incumbent", "incumbent_competitor", "incumbents", "influencer", "informal_logistics", "informal_logistics_partner", "institutional_guardian", "internal_operations", "internal_operator", "investor", "investor_board", "investors", "journalist", "journalists", "judiciary", "judiciary_court", "labor_union", "labour_union", "land_custodian", "land_owner", "landlord", "landowner", "lender", "lender_creditor", "lenders", "market_queen", "media", "media_press", "member", "micro_logistics", "mobile_money_agent", "organized_labour", "platform_partner", "political_guardian", "press", "public_official", "regulator", "regulatory_body", "religious_leader", "research_respondent_group", "retail_partner", "retailer", "retailer_partner", "revenue_authority", "sacco_member", "school", "service_provider", "shareholder", "shareholders", "supplier", "suppliers", "tax_authority", "tax_revenue_authority", "teacher", "traditional_chief", "union", "upstream_supplier", "upstream_vendor", "vc", "vendor", "vendors", "venture_capital", "worker_association", "works_council" ] } }, "evidence_pack": { "type": "array", "items": { "$ref": "#/$defs/EvidenceItem" } }, "compiled_pack": { "type": "object", "properties": { "public_reality_pack": { "type": "array", "items": { "$ref": "#/$defs/EvidenceItem" } }, "telemetry_proxy_pack": { "type": "array", "items": { "$ref": "#/$defs/EvidenceItem" } }, "localized_observed_pack": { "type": "array", "items": { "$ref": "#/$defs/EvidenceItem" } }, "survey_pack": { "type": "array", "items": { "$ref": "#/$defs/EvidenceItem" } }, "retail_audit_pack": { "type": "array", "items": { "$ref": "#/$defs/EvidenceItem" } }, "ngo_program_pack": { "type": "array", "items": { "$ref": "#/$defs/EvidenceItem" } }, "evaluation_pack": { "type": "array", "items": { "$ref": "#/$defs/EvidenceItem" } }, "administrative_data_pack": { "type": "array", "items": { "$ref": "#/$defs/EvidenceItem" } }, "partner_network_pack": { "type": "array", "items": { "$ref": "#/$defs/EvidenceItem" } }, "social_listening_pack": { "type": "array", "items": { "$ref": "#/$defs/EvidenceItem" } } } }, "unit_economics": { "type": [ "object", "null" ], "properties": { "ltv_cac_ratio": { "type": [ "number", "null" ], "minimum": 0, "maximum": 100 }, "cac_ltv_ratio": { "type": [ "number", "null" ], "minimum": 0, "maximum": 100 }, "payback_period_months": { "type": [ "number", "null" ], "minimum": 0 }, "gross_margin_percent": { "type": [ "number", "null" ], "minimum": -100, "maximum": 100 }, "capital_runway_months": { "type": [ "number", "null" ], "minimum": 0 }, "monthly_burn_usd": { "type": [ "number", "null" ], "minimum": 0, "not": { "maximum": 0 } }, "cash_conversion_cycle_days": { "type": [ "number", "null" ], "minimum": 0, "maximum": 730 }, "data_confidence": { "type": [ "string", "null" ], "enum": [ "audited_financials", "projected", "management_estimate" ] } }, "additionalProperties": true }, "financial_context": { "type": [ "object", "null" ], "properties": { "runway_months": { "type": [ "number", "null" ], "minimum": 0, "maximum": 1200 }, "ltv_cac_ratio": { "type": [ "number", "null" ], "minimum": 0, "maximum": 100 }, "gross_margin_pct": { "type": [ "number", "null" ], "minimum": -100, "maximum": 100 }, "monthly_burn_local_currency": { "type": [ "number", "null" ], "minimum": 0 } }, "additionalProperties": true }, "competitive_context": { "type": [ "object", "null" ], "properties": { "incumbent_share_pct": { "type": [ "number", "null" ], "minimum": 0, "maximum": 100 }, "switching_cost_index_0_100": { "type": [ "number", "null" ], "minimum": 0, "maximum": 100 }, "price_war_risk": { "type": [ "string", "null" ], "enum": [ "low", "moderate", "high", "extreme" ] } }, "additionalProperties": true }, "behavioral_signals": { "type": [ "object", "null" ], "properties": { "monthly_churn_rate": { "type": [ "number", "null" ], "minimum": 0, "maximum": 1 }, "dau": { "type": [ "number", "null" ], "minimum": 0 } }, "additionalProperties": true }, "operational_readiness": { "type": [ "object", "null" ], "properties": { "sla_uptime_pct_90d": { "type": [ "number", "null" ], "minimum": 0, "maximum": 100 } }, "additionalProperties": true }, "sentiment_velocity": { "type": [ "object", "null" ], "properties": { "delta_trust": { "type": [ "number", "null" ], "minimum": -100, "maximum": 100 }, "delta_permission": { "type": [ "number", "null" ], "minimum": -100, "maximum": 100 } }, "additionalProperties": true }, "network_economics": { "type": [ "object", "null" ], "additionalProperties": true, "description": "Presence-only declared context in the current kernel; no metric keys are independently evaluated." }, "b2b_context": { "type": [ "object", "null" ], "additionalProperties": true, "description": "Presence-only declared context in the current kernel; no procurement authorization is inferred." }, "scaling_physics": { "type": [ "object", "null" ], "properties": { "expected_embeddedness_decay_at_scale_pct": { "type": [ "number", "null" ], "minimum": 0, "maximum": 100 } }, "additionalProperties": true }, "market_education_profile": { "type": [ "object", "null" ], "properties": { "phase": { "type": [ "string", "null" ], "enum": [ "discovery", "education", "early_adoption", "mainstream" ] } }, "additionalProperties": true }, "mvr_scores": { "type": "object", "properties": { "executive": { "anyOf": [ { "type": "object", "additionalProperties": { "type": "number", "minimum": 0, "maximum": 100 } }, { "type": "number", "minimum": 0, "maximum": 100 } ], "description": "Prefer dimension-keyed scores. Legacy bounded scalar executive score is normalized separately and cannot fill missing evidence dimensions." }, "dimensions": { "type": "object", "additionalProperties": { "type": "number", "minimum": 0, "maximum": 100 } }, "permission": { "type": "number", "minimum": 0, "maximum": 100 }, "trust": { "type": "number", "minimum": 0, "maximum": 100 }, "belonging": { "type": "number", "minimum": 0, "maximum": 100 }, "embeddedness": { "type": "number", "minimum": 0, "maximum": 100 }, "reciprocity": { "type": "number", "minimum": 0, "maximum": 100 }, "cultural_fit": { "type": "number", "minimum": 0, "maximum": 100 }, "guardian_strength": { "type": "number", "minimum": 0, "maximum": 100 }, "continuity": { "type": "number", "minimum": 0, "maximum": 100 }, "channel_permission": { "type": "number", "minimum": 0, "maximum": 100 }, "infrastructural_intimacy": { "type": "number", "minimum": 0, "maximum": 100 }, "absence_sensitivity": { "type": "number", "minimum": 0, "maximum": 100 }, "narrative_looping": { "type": "number", "minimum": 0, "maximum": 100 }, "whispered_credibility": { "type": "number", "minimum": 0, "maximum": 100 }, "fractal_trust": { "type": "number", "minimum": 0, "maximum": 100 }, "cultural_calibration": { "type": "number", "minimum": 0, "maximum": 100 } }, "additionalProperties": true }, "case_id": { "type": "string" }, "allow_non_decisive_operator_review": { "type": "boolean" }, "baseline_period": { "type": "string", "enum": [ "12m", "24m", "36m" ] }, "backtest_window": { "type": "object", "properties": { "start": { "type": "string", "description": "ISO calendar date or timestamp." }, "end": { "type": "string", "description": "ISO calendar date or timestamp." } }, "additionalProperties": true, "required": [ "start", "end" ] }, "sector_metrics": { "type": [ "object", "null" ], "properties": { "sector": { "type": "string", "maxLength": 96 }, "metrics": { "type": "object", "maxProperties": 60, "additionalProperties": { "anyOf": [ { "type": "string" }, { "type": "number" }, { "type": "boolean" } ], "nullable": true } } }, "additionalProperties": true, "required": [ "metrics" ] }, "project_id": { "type": "string", "minLength": 1, "description": "Tenant/workspace project context. Equivalent to subject.project_id; conflicting identifiers are rejected. Memory never supplies evidence or permission." }, "use_project_memory": { "type": "boolean", "description": "Defaults to true when a project ID is supplied. Set false to disable contextual defaults." }, "project_memory": { "type": "boolean", "description": "Compatibility alias for use_project_memory; either false disables loading." }, "backtest_mode": { "type": "boolean", "description": "When true, response echoes backtest_mode and optional t0_date for replay transparency." }, "t0_date": { "type": "string", "description": "Backtest as-of date echoed when backtest_mode is true." } }, "$defs": { "EvidenceItem": { "type": "object", "additionalProperties": true, "description": "Extensible source metadata. Unknown item-level field names receive non-blocking input_interpretation notices on successful licensed evidence responses; acceptance is not proof that a control was evaluated. Suggested names require checking source facts and are never applied automatically. Nested open metadata is not recursively classified by this notice mechanism. Recovery: Codes: FIELD_PROVENANCE_REQUIRED,FIELD_PROVENANCE_CONFLICT,FIELDWORK_CAPACITY_CONTRADICTION,SOURCE_INDEPENDENCE_CONTRADICTION,SOURCE_VERIFICATION_CONTRADICTION,FIELD_SOURCE_MODALITY_CONFLICT,DECISION_GEOGRAPHY_SCOPE_REQUIRED,DECISION_SCOPE_REQUIRED,DECISION_SCOPE_REVIEW_REQUIRED,DECISION_SCOPE_CROSS_CHECK_LIMIT,SOURCE_EXTRACTION_INVALID,SOURCE_EXTRACTION_REFERENCE_CONFLICT,ADVERSE_SOURCE_REVIEW_REQUIRED,INVALID_CLAIM_INPUT,OUTPUT_RECEIPT_NOT_REQUEST_AUTHORITY,ARTIFACT_ROLE_NOT_SOURCE_EVIDENCE. HTTP 422: details/validation_errors; fix missing_fields. Never invent facts. These codes do not authenticate sources or authorize action. /docs/mcp-integration.md.", "x-compatible-item-field-names": [ "provenance", "privacy", "modality", "pack_type", "source_type", "source_family", "source_locator", "source_hash", "upstream_source_ids", "parent_source_ids", "support_links", "source_relationship", "claim_id", "collected_at", "submitted_at", "public_metric_period_end", "collection_period_start", "collection_period_end", "score_scale", "value_scale", "scale", "category", "subject", "demographics", "independence_metadata", "dependence_metadata", "independence_group_id", "dependency_group_id", "independence_basis", "event_id", "dataset_id", "method_id", "instrument_id", "collector_id", "error_process_id", "source_review", "review", "reviewer_id", "extraction_method", "extraction_confidence" ], "properties": { "id": { "type": "string" }, "evidence_id": { "type": "string" }, "claim": { "type": "string" }, "load_bearing": { "type": "boolean" }, "is_load_bearing": { "type": "boolean" }, "source_date": { "type": "string", "minLength": 4, "maxLength": 32, "description": "Declared source date at its actual precision: YYYY, YYYY-MM, YYYY-MM-DD, or ISO timestamp with seconds and timezone (up to 6 fractional digits). Years 0001-9999; real calendar dates only. Partial dates describe inclusive calendar bounds, never an invented day. Source truth and current applicability remain unverified. Metadata only: typed scoring still requires an exact freshness date and excludes partial-date or range-bearing items." }, "source_date_range": { "type": "object", "additionalProperties": false, "required": [ "earliest", "latest" ], "properties": { "earliest": { "type": "string", "minLength": 4, "maxLength": 32, "description": "Declared source date at its actual precision: YYYY, YYYY-MM, YYYY-MM-DD, or ISO timestamp with seconds and timezone (up to 6 fractional digits). Years 0001-9999; real calendar dates only. Partial dates describe inclusive calendar bounds, never an invented day. Source truth and current applicability remain unverified." }, "latest": { "type": "string", "minLength": 4, "maxLength": 32, "description": "Declared source date at its actual precision: YYYY, YYYY-MM, YYYY-MM-DD, or ISO timestamp with seconds and timezone (up to 6 fractional digits). Years 0001-9999; real calendar dates only. Partial dates describe inclusive calendar bounds, never an invented day. Source truth and current applicability remain unverified." } }, "description": "Optional inclusive declared bounds, usable without source_date. Both endpoints must have the same precision and be ordered. Every supplied source_date/freshness_date must contain the whole range; an exact timestamp cannot be widened. Aliases must agree before narrowing. Unknown dates are not clipped to the analysis date. Bounds are declarations, not source verification." }, "source_url": { "type": "string" }, "source_doc_id": { "type": "string" }, "sample_size": { "type": "integer", "minimum": 1, "maximum": 9007199254740991, "description": "Actual sample for collector-administered evidence, including groups. Sample aliases must agree; never invent counts for documentary or self-administered sources." }, "population_size": { "type": "integer", "minimum": 1 }, "population_definition": { "type": "string" }, "sampling_method": { "type": "string", "description": "Use census for a declared complete finite population; this does not override weighted sample admission." }, "is_complete_population": { "type": "boolean" }, "census": { "type": "boolean", "description": "Alias for is_complete_population. Only literal true with consistent positive integer sample_size = population_size enables the disclosure." }, "collection_context": { "type": "object", "additionalProperties": true, "description": "Source-grounded collection declarations, not source authentication. Unknown facts must remain missing; do not invent values to pass. Field decision use requires source modality, collector relationship, interview mode, source-document identity and an explicit parent-source list. Collector-administered modes require staffing, duration, available minutes per collector and sample size. Group modes additionally require session_count, participants_per_session, session_duration_minutes and collectors_per_session, never inferred from an individual interview duration. Online, observation and administrative_record modes require collection_administration; self-administered online and automated observation/record sources do not need invented collector capacity. Explicit public/documentary origins are not caller fieldwork solely because evidence_type is survey; conflicting explicit field origins still block. Independent verification labels require a separate reviewer relationship; persisted review is still checked separately.", "properties": { "source_modality": { "type": "string", "enum": [ "direct_observation", "documentary", "secondary_summary", "unknown" ] }, "collector_relationship": { "type": "string", "enum": [ "independent", "employee", "company_staff", "internal", "contractor", "partner", "self_collected", "unknown" ], "pattern": "\\S" }, "reviewer_relationship": { "type": "string", "enum": [ "independent", "employee", "company_staff", "internal", "contractor", "partner", "self_collected", "unknown" ] }, "interview_mode": { "type": "string", "enum": [ "face_to_face", "telephone", "online", "focus_group", "group_interview", "observation", "administrative_record", "unknown" ], "pattern": "\\S" }, "collection_administration": { "type": "string", "enum": [ "collector_administered", "self_administered", "automated", "unknown" ], "description": "Source-grounded administration, required for online, observation and administrative_record modes. self_administered is supported for online; automated for observation or administrative_record. Face-to-face, telephone and group modes are collector-administered and cannot opt out." }, "enumerator_count": { "type": "integer", "minimum": 1, "maximum": 9007199254740991 }, "interview_duration_minutes": { "type": "number", "exclusiveMinimum": true, "description": "Collector time per individual interview or per observed/processed sample record for collector-administered non-group modes.", "minimum": 0 }, "fieldwork_window_minutes": { "type": "number", "exclusiveMinimum": true, "description": "Total available collection minutes per collector across the entire period, not daily or team-person-minutes.", "minimum": 0 }, "session_count": { "type": "integer", "minimum": 1, "maximum": 9007199254740991, "description": "Actual number of group sessions in the source records." }, "participants_per_session": { "type": "integer", "minimum": 1, "maximum": 9007199254740991, "description": "Source-grounded maximum participants in any session. Sample size cannot exceed session_count times this bound; no default group size is assumed." }, "session_duration_minutes": { "type": "number", "exclusiveMinimum": true, "description": "Source-recorded duration of each group session in this declaration, not an alias for individual interview duration.", "minimum": 0 }, "collectors_per_session": { "type": "integer", "minimum": 1, "maximum": 9007199254740991, "description": "Collectors required concurrently for each group session, drawn from enumerator_count. No default facilitator count is assumed." }, "sample_size": { "type": "integer", "minimum": 1, "maximum": 9007199254740991 }, "source_extraction": { "type": "object", "additionalProperties": false, "required": [ "source_ref", "fields" ], "description": "Optional caller-supplied second reading of source facts for conflict comparison only. Not independently authenticated; cannot supply missing primary declarations or establish source authenticity.", "properties": { "source_ref": { "type": "string", "minLength": 1, "maxLength": 512 }, "fields": { "type": "object", "additionalProperties": false, "properties": { "source_modality": { "type": "string", "enum": [ "direct_observation", "documentary", "secondary_summary", "unknown" ] }, "collector_relationship": { "type": "string", "enum": [ "independent", "employee", "company_staff", "internal", "contractor", "partner", "self_collected", "unknown" ] }, "reviewer_relationship": { "type": "string", "enum": [ "independent", "employee", "company_staff", "internal", "contractor", "partner", "self_collected", "unknown" ] }, "interview_mode": { "type": "string", "enum": [ "face_to_face", "telephone", "online", "focus_group", "group_interview", "observation", "administrative_record", "unknown" ] }, "collection_administration": { "type": "string", "enum": [ "collector_administered", "self_administered", "automated", "unknown" ], "description": "Source-grounded administration, required for online, observation and administrative_record modes. self_administered is supported for online; automated for observation or administrative_record. Face-to-face, telephone and group modes are collector-administered and cannot opt out." }, "enumerator_count": { "type": "integer", "minimum": 1, "maximum": 9007199254740991 }, "interview_duration_minutes": { "type": "number", "exclusiveMinimum": true, "description": "Collector time per individual interview or per observed/processed sample record for collector-administered non-group modes.", "minimum": 0 }, "fieldwork_window_minutes": { "type": "number", "exclusiveMinimum": true, "description": "Total available collection minutes per collector across the entire period, not daily or team-person-minutes.", "minimum": 0 }, "session_count": { "type": "integer", "minimum": 1, "maximum": 9007199254740991, "description": "Actual number of group sessions in the source records." }, "participants_per_session": { "type": "integer", "minimum": 1, "maximum": 9007199254740991, "description": "Source-grounded maximum participants in any session. Sample size cannot exceed session_count times this bound; no default group size is assumed." }, "session_duration_minutes": { "type": "number", "exclusiveMinimum": true, "description": "Source-recorded duration of each group session in this declaration, not an alias for individual interview duration.", "minimum": 0 }, "collectors_per_session": { "type": "integer", "minimum": 1, "maximum": 9007199254740991, "description": "Collectors required concurrently for each group session, drawn from enumerator_count. No default facilitator count is assumed." }, "sample_size": { "type": "integer", "minimum": 1, "maximum": 9007199254740991 } } } } }, "collection_tool": { "type": "string", "enum": [ "structured_interview_protocol", "expert_ethnographic_observation", "field_observation", "survey_platform_verified", "survey_paper_based", "key_informant_interview", "team_consensus_estimate", "founder_intuition", "inferred_from_secondary", "direct", "inferred", "secondary_source", "corporate_telemetry", "database_aggregation", "expert_opinion", "intercept_interview" ] }, "population_size": { "type": "integer", "minimum": 1 }, "population_definition": { "type": "string" }, "sampling_method": { "type": "string", "description": "Use census for a declared complete finite population; this does not override weighted sample admission." }, "is_complete_population": { "type": "boolean" }, "census": { "type": "boolean", "description": "Alias for is_complete_population. Only literal true with consistent positive integer sample_size = population_size enables the disclosure." } } }, "evidence_type": { "type": "string", "enum": [ "public_filing", "survey", "interview", "observation", "telemetry", "admin_data", "evaluation", "retail_audit", "social_listening", "partner_network", "program_monitoring" ] }, "entity_archetype": { "type": "string", "enum": [ "telecom_operator", "mobile_money_operator", "fintech_platform", "financial_services_bank", "fintech_lending", "logistics_platform", "energy_utility", "extractives_operator", "real_estate_construction", "education_provider", "passenger_mobility", "b2b_saas_platform", "healthtech_platform", "insurance_platform", "fmcg_brand", "retail_chain", "ecommerce_platform", "manufacturer", "distributor_network", "ngo", "development_program", "public_institution", "survey_dataset", "solo_entrepreneur", "family_business", "cooperative_sacco", "cross_border_trader", "university_spinout", "diaspora_venture", "creator_economy_individual", "agritech_aggregator", "impact_enterprise", "religious_institution", "chama_savings_group" ] }, "source_class": { "type": "string", "enum": [ "entity_reported", "independently_audited", "regulator_published", "administrative_record", "probability_sample_survey", "nonprobability_survey", "structured_field_research", "third_party_evaluation", "retail_audit", "telemetry_internal", "media_reported" ], "description": "Source-evidence classes only. Model-inferred artifacts are context and are rejected with ARTIFACT_ROLE_NOT_SOURCE_EVIDENCE." }, "source_grade": { "type": "string", "enum": [ "A", "B", "C", "D" ] }, "stakeholder_class": { "type": "string", "enum": [ "agent", "anchor_customer", "bank_lender", "beneficiary", "board", "board_member", "chama_member", "channel_gatekeeper", "chief", "civil_society_org", "clinic", "community_guardian", "community_leader", "competitor", "competitors", "consumer", "cooperative_member", "court", "courts", "creditor", "creditors", "customary_land_authority", "customer", "customs", "customs_authority", "distributor", "donor", "donor_guardian", "enumerator", "farmer", "field_agent", "field_supervisor", "gatekeeper", "guarantor", "guardian", "guardian_node", "implementing_partner", "incumbent", "incumbent_competitor", "incumbents", "influencer", "informal_logistics", "informal_logistics_partner", "institutional_guardian", "internal_operations", "internal_operator", "investor", "investor_board", "investors", "journalist", "journalists", "judiciary", "judiciary_court", "labor_union", "labour_union", "land_custodian", "land_owner", "landlord", "landowner", "lender", "lender_creditor", "lenders", "market_queen", "media", "media_press", "member", "micro_logistics", "mobile_money_agent", "organized_labour", "platform_partner", "political_guardian", "press", "public_official", "regulator", "regulatory_body", "religious_leader", "research_respondent_group", "retail_partner", "retailer", "retailer_partner", "revenue_authority", "sacco_member", "school", "service_provider", "shareholder", "shareholders", "supplier", "suppliers", "tax_authority", "tax_revenue_authority", "teacher", "traditional_chief", "union", "upstream_supplier", "upstream_vendor", "vc", "vendor", "vendors", "venture_capital", "worker_association", "works_council" ] }, "guardian_tier": { "type": "string", "enum": [ "macro_regulator", "meso_community", "micro_street" ], "description": "Guardian role classification, not an adverse score setting. Only guardian evidence activates guardian-specific analysis; stance, observed substance and actual veto authority determine applicable gates. A tier change need not change the verdict." }, "evidence_origin": { "type": "string", "enum": [ "public_osint", "field_research", "mixed", "corporate_telemetry", "platform_telemetry" ], "description": "Explicit public documentary survey tables do not require caller fieldwork metadata or become direct field coverage. Contradictory explicit field origins still require reconciliation." }, "collection_method": { "type": "string", "enum": [ "structured_interview_protocol", "expert_ethnographic_observation", "field_observation", "survey_platform_verified", "survey_paper_based", "key_informant_interview", "team_consensus_estimate", "founder_intuition", "inferred_from_secondary", "direct", "inferred", "secondary_source", "corporate_telemetry", "database_aggregation", "expert_opinion", "intercept_interview" ] }, "source_confidence": { "type": "string", "enum": [ "high", "medium", "low" ] }, "stance": { "type": "string", "enum": [ "hostile", "neutral", "friendly", "opposed" ], "description": "Declared stakeholder stance. Opposed or hostile load-bearing evidence requires stakeholder review even when linked as direct_support. This does not rewrite the factual claim relationship or authenticate the source." }, "verification_status": { "type": "string", "enum": [ "unverified", "self_reported", "document_supported", "independently_verified", "verified", "disputed" ], "description": "Caller declaration, not independent verification. No confidence boost from this label. Disputed evidence blocks authorization until reconciled or segregated." }, "freshness_date": { "type": "string", "format": "date" }, "evidence_geography": { "type": "object", "properties": { "country": { "type": "string", "enum": [ "AD", "AE", "AF", "AG", "AI", "AL", "AM", "AO", "AQ", "AR", "AS", "AT", "AU", "AW", "AX", "AZ", "BA", "BB", "BD", "BE", "BF", "BG", "BH", "BI", "BJ", "BL", "BM", "BN", "BO", "BQ", "BR", "BS", "BT", "BV", "BW", "BY", "BZ", "CA", "CC", "CD", "CF", "CG", "CH", "CI", "CK", "CL", "CM", "CN", "CO", "CR", "CU", "CV", "CW", "CX", "CY", "CZ", "DE", "DJ", "DK", "DM", "DO", "DZ", "EC", "EE", "EG", "EH", "ER", "ES", "ET", "FI", "FJ", "FK", "FM", "FO", "FR", "GA", "GB", "GD", "GE", "GF", "GG", "GH", "GI", "GL", "GM", "GN", "GP", "GQ", "GR", "GS", "GT", "GU", "GW", "GY", "HK", "HM", "HN", "HR", "HT", "HU", "ID", "IE", "IL", "IM", "IN", "IO", "IQ", "IR", "IS", "IT", "JE", "JM", "JO", "JP", "KE", "KG", "KH", "KI", "KM", "KN", "KP", "KR", "KW", "KY", "KZ", "LA", "LB", "LC", "LI", "LK", "LR", "LS", "LT", "LU", "LV", "LY", "MA", "MC", "MD", "ME", "MF", "MG", "MH", "MK", "ML", "MM", "MN", "MO", "MP", "MQ", "MR", "MS", "MT", "MU", "MV", "MW", "MX", "MY", "MZ", "NA", "NC", "NE", "NF", "NG", "NI", "NL", "NO", "NP", "NR", "NU", "NZ", "OM", "PA", "PE", "PF", "PG", "PH", "PK", "PL", "PM", "PN", "PR", "PS", "PT", "PW", "PY", "QA", "RE", "RO", "RS", "RU", "RW", "SA", "SB", "SC", "SD", "SE", "SG", "SH", "SI", "SJ", "SK", "SL", "SM", "SN", "SO", "SR", "SS", "ST", "SV", "SX", "SY", "SZ", "TC", "TD", "TF", "TG", "TH", "TJ", "TK", "TL", "TM", "TN", "TO", "TR", "TT", "TV", "TW", "TZ", "UA", "UG", "UM", "US", "UY", "UZ", "VA", "VC", "VE", "VG", "VI", "VN", "VU", "WF", "WS", "YE", "YT", "ZA", "ZM", "ZW" ] }, "region": { "type": "string" }, "city": { "type": "string" }, "district": { "type": "string", "pattern": "\\S" }, "districts": { "type": "array", "items": { "type": "string", "pattern": "\\S" } }, "town_or_zone": { "type": "string" } }, "description": "Use a supported ISO country code, not a country name. Explicit districts declare source coverage, not authenticity or representativeness. Do not relabel geography to match the decision." }, "geography": { "anyOf": [ { "type": "string" }, { "type": "object", "properties": { "district": { "type": "string", "pattern": "\\S" }, "districts": { "type": "array", "items": { "type": "string", "pattern": "\\S" } } }, "additionalProperties": true } ] }, "temporal": { "type": "object", "properties": { "freshness_date": { "type": "string", "description": "ISO calendar date for the collection/freshness alias. Must satisfy the same runtime date checks as freshness_date." }, "expired": { "type": "boolean", "description": "Literal true requires review for decision-relevant evidence, regardless of a recent source date." } } }, "public_metric_scope": { "type": "string", "enum": [ "entity_scale", "country_scale", "regional_scale", "city_scale", "site_scale" ] }, "public_metrics": { "type": "object" }, "structured_values": { "type": "object", "description": "Ingestible field-observed MVR dimension values. Canonical production scale is 0-100. Accepted core keys: permission, trust, belonging, embeddedness, reciprocity, cultural_fit, guardian_strength, continuity, channel_permission, infrastructural_intimacy, absence_sensitivity, narrative_looping, whispered_credibility, fractal_trust, cultural_calibration. Agent-safety note: if at least two valid core dimensions on the same evidence item are all between 0 and 1, the worker normalizes them from fractional 0-1 to 0-100 before scoring; production clients should still send 0-100 to avoid ambiguity. Do not submit derived concepts such as evidence_completeness, market_carry, local_legitimacy; submit the listed underlying dimensions instead.", "additionalProperties": { "type": "number", "minimum": 0, "maximum": 100 }, "x-ingestible-dimensions": [ "permission", "trust", "belonging", "embeddedness", "reciprocity", "cultural_fit", "guardian_strength", "continuity", "channel_permission", "infrastructural_intimacy", "absence_sensitivity", "narrative_looping", "whispered_credibility", "fractal_trust", "cultural_calibration" ], "x-derived-concepts": [ "evidence_completeness", "market_carry", "local_legitimacy" ], "x-canonical-scale": "0-100", "x-fraction-scale-normalization": "unambiguous 0-1 core-dimension rows are normalized to 0-100" }, "structured_values_scale": { "type": "string", "description": "Optional hint for agents. Use '0-1 fraction' only when sending fractional structured_values; otherwise omit and send canonical 0-100 scores." }, "behavioral_values": { "type": "object", "additionalProperties": false, "properties": { "30_day_active_retention_percent": { "type": "number", "minimum": 0, "maximum": 100 } }, "description": "Supported on corporate telemetry. The current check pairs high consumer field permission with low 30_day_active_retention_percent under the configured maturity policy, caps scale at pilot_ready and emits severe_evidence_dissonance_survey_vs_telemetry in scale_recommendation.blueprint_codes. A lower existing pilot_only ceiling need not change. This is not a general trust/churn causal inference; unspecified churn, retention and frequency keys are rejected." }, "structured_values_provenance": { "type": "object", "additionalProperties": { "type": "string", "enum": [ "observed", "proxy-derived", "imputed" ] }, "description": "Per-dimension map using exact keys present in structured_values, for example {trust:\"observed\",permission:\"imputed\"}. input_score_provenance is not a blanket override and is rejected as an unknown dimension. Provenance affects admitted support and weights; other gates may keep headline scores or confidence unchanged." }, "human_reviewed": { "type": "boolean", "description": "Caller-declared review required for AI-extracted material before strict or decisive use. Not identity verification, a signature, authenticated reviewer approval or independent source verification." }, "review_status": { "type": "string", "enum": [ "pending", "approved", "accepted", "verified", "reviewed", "rejected" ] }, "reviewed_by": { "type": "string", "description": "Caller-supplied reviewer name for AI-extracted material when human_reviewed=true. The name is not authenticated; supplying it does not establish identity, independence or that review occurred." }, "reviewed_at": { "type": "string", "format": "date" }, "human_review": { "type": "object", "description": "Optional structured review record; may include by/reviewer_id, status, and reviewed_at." }, "organ_attestation": { "type": "object", "description": "MVR Examiner or other organ-produced evidence attestation. The deterministic kernel treats unreviewed organ evidence as imputed/non-decisive." }, "_verifier_attestation": { "type": "object", "description": "Verifier-organ attestation for extraction review. Internal/audit use; unreviewed AI extraction remains non-decisive." }, "privacy_envelope": { "type": "object", "properties": { "contains_pii": { "type": "boolean" }, "contains_sensitive_personal_data": { "type": "boolean" }, "consent_basis": { "type": "string", "enum": [ "consent", "contract", "legitimate_interest", "public_interest", "legal_obligation", "not_applicable" ] }, "retention_class": { "type": "string", "enum": [ "session_only", "30d", "90d", "1y", "7y", "contractual" ] }, "redaction_status": { "type": "string", "enum": [ "raw", "minimized", "redacted", "aggregated" ] }, "safe_for_modeling": { "type": "boolean" } } }, "uncertainty_envelope": { "type": "object", "additionalProperties": false, "properties": { "source_uncertainty": { "type": "number", "minimum": 0, "maximum": 1 }, "sampling_uncertainty": { "type": "number", "minimum": 0, "maximum": 1 }, "extraction_uncertainty": { "type": "number", "minimum": 0, "maximum": 1 }, "temporal_uncertainty": { "type": "number", "minimum": 0, "maximum": 1 }, "archetype_fit_uncertainty": { "type": "number", "minimum": 0, "maximum": 1 }, "disagreement_uncertainty": { "type": "number", "minimum": 0, "maximum": 1 }, "interval_80": { "type": "array", "minItems": 2, "maxItems": 2, "items": { "type": "number", "minimum": 0, "maximum": 100 } }, "score_point_estimate": { "type": "number", "minimum": 0, "maximum": 100 }, "basis": { "type": "string" } }, "description": "Named 0-1 components influence evidence weighting. interval_80, score_point_estimate and basis are caller-supplied descriptions, not calibrated output intervals or gate overrides. Unknown component names are rejected; uniform reweighting or another cap can leave headline confidence unchanged." }, "survey_payload": { "type": "object", "properties": { "survey_name": { "type": "string" }, "population_definition": { "type": "string" }, "sample_frame": { "type": "string" }, "sampling_method": { "type": "string", "enum": [ "probability", "quota", "convenience", "panel", "census" ] }, "sample_size": { "type": "number", "exclusiveMinimum": 0 }, "effective_sample_size": { "type": "number", "exclusiveMinimum": 0 }, "response_rate_pct": { "type": "number", "minimum": 0, "maximum": 100 }, "geo_resolution": { "type": "string", "enum": [ "national", "regional", "district", "ward", "site" ] }, "fieldwork_start": { "type": "string", "format": "date" }, "fieldwork_end": { "type": "string", "format": "date" } }, "description": "For survey evidence, include survey_name, population_definition, sampling_method and sample_frame. Panel and census are accepted sampling methods. Census additionally requires consistent declared population_size and sample_size; it never bypasses weighted admission or establishes representativeness." }, "payload": { "type": "object", "description": "Generic typed evidence payload, including telemetry or evaluation details. Retains supplied context only; prose does not become observed numeric scores or authenticated proof. Evaluation payloads need evaluator_name.", "properties": { "evaluator_name": { "type": "string" }, "evaluation_date": { "type": "string", "format": "date" }, "methodology": { "type": "string" } } }, "program_payload": { "type": "object", "required": [ "program_name", "beneficiary_definition" ], "properties": { "program_name": { "type": "string", "minLength": 1 }, "beneficiary_definition": { "type": "string", "minLength": 1 } } }, "admin_data_payload": { "type": "object", "required": [ "collection_authority" ], "properties": { "collection_authority": { "type": "string", "minLength": 1 }, "extraction_date": { "type": "string", "format": "date" }, "reporting_completeness_pct": { "type": "number", "minimum": 0, "maximum": 100 } } }, "retail_audit_payload": { "type": "object", "required": [ "outlet_frame", "coverage_universe", "stock_check_method" ], "properties": { "outlet_frame": { "type": "string", "minLength": 1 }, "coverage_universe": { "type": "string", "minLength": 1 }, "stock_check_method": { "type": "string", "minLength": 1 } } }, "provenance_ledger": { "type": "object", "properties": { "source_family": { "type": "string" }, "collection_date": { "type": "string", "description": "ISO calendar date for the collection/freshness alias. Must satisfy the same runtime date checks as freshness_date." }, "source_doc_id": { "type": "string" }, "source_locator": { "type": "string" }, "extraction_method": { "type": "string", "enum": [ "human", "deterministic_parser", "llm_inferred", "automated_query" ] }, "extraction_confidence": { "type": "number", "minimum": 0, "maximum": 1 }, "compiler_stage": { "type": "string" }, "data_integrity": { "type": "object", "additionalProperties": false, "properties": { "variance_anomaly_detected": { "type": "boolean", "description": "Caller-declared variance anomaly, not a numeric variance score. True constrains the decision ceiling and requires source corroboration." }, "bot_or_farm_probability": { "type": "number", "minimum": 0, "maximum": 1, "description": "Caller-supplied finite 0-1 bot/farm-risk estimate from an upstream assessment. AMOS does not calculate this probability from source prose." } }, "description": "Optional declared integrity signals, honored for flat evidence and compiled lanes. Unknown keys, null, invalid types and out-of-range values are rejected. Omission or an empty object means no assessment supplied, not a clean bill of health. In client_safe read scale_recommendation.blueprint_codes and decision_authorization, including data_integrity_gate.blocking_alerts when blocked. data_quality.integrity_alerts is an internal/full diagnostic path and may be omitted by projection. A confidence or candidate label alone is not the gate result. These are configured review controls, not independently verified anti-fraud detection." } } }, "source_artifacts": { "type": "array", "maxItems": 20, "items": { "type": "object", "required": [ "artifact_id", "media_type" ], "properties": { "artifact_id": { "type": "string" }, "media_type": { "type": "string" }, "storage_uri": { "type": "string" }, "sha256": { "type": "string" }, "extraction_method": { "type": "string", "enum": [ "human", "deterministic_parser", "llm_inferred", "automated_query" ] }, "extractor_version": { "type": "string" }, "extracted_at": { "type": "string", "format": "date-time" }, "human_reviewed": { "type": "boolean" } } } } } } } }