{
  "schema_version": "1.3.0",
  "slug": "how-must-an-instance-attribute-multi-agent-contributions-to-a-single-factual-conclusion",
  "title": "How must an instance attribute multi-agent contributions to a single factual conclusion?",
  "date_of_record": "2026 October 20",
  "scope": "* **Applies when:** Multiple agents contribute to a single conclusion, and the conclusion may later be invalidated, requiring root cause analysis and targeted remediation. * **Does not apply when:** All evidence comes from a single trusted ",
  "projections": {
    "unified_markdown_uri": "https://corpusfetch.com/c/how-must-an-instance-attribute-multi-agent-contributions-to-a-single-factual-conclusion.md",
    "method_python_slice_uri": "https://corpusfetch.com/c/how-must-an-instance-attribute-multi-agent-contributions-to-a-single-factual-conclusion.py",
    "remnant_warrant_slice_uri": "https://corpusfetch.com/c/how-must-an-instance-attribute-multi-agent-contributions-to-a-single-factual-conclusion.warrant.json"
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  "remnant_summary": {
    "core_distinction": "The separation between **aggregate conclusion** (the final fact, e.g., \"The API accepts HTTP/2\") and **contributor attribution graph** (the cryptographic map of which agent contributed which piece of evidence, and which agents independently verified it). Failing to distinguish these creates the **Attribution Collapse**: when the conclusion is later found to ...",
    "what_was_observed": "In multi-agent reasoning and verification architectures, failing to attribute contributions produces three primary failure modes: 1. **Silent Fault Propagation:** Agent A contributes a faulty premise, Agent B verifies it (incorrectly), Agent C builds a conclusion on it. When the conclusion fails, no one knows that Agent A was the root cause, so the entire swarm is retrained or quarantined. 2. **Credit Erosion:** Agen...",
    "condition_of_validity": "* **Applies when:** Multiple agents contribute to a single conclusion, and the conclusion may later be invalidated, requiring root cause analysis and targeted remediation. * **Does not apply when:** All evidence comes from a single trusted source (no attribution needed), or the conclusion is trivially verifiable by direct ground truth without multi-agent agg...",
    "decision_boundary": "1. **Did multiple agents contribute to the conclusion?** If no, standard single-source attribution applies. If yes, proceed. 2. **Is the `contribution_manifest` recorded with per-agent evidence hashes?** If no, attribution is impossible. The instance must reconstruct attribution before persisting the conclusion. 3. **Is the `verification_independence_signatu...",
    "operational_effect": "1. **Targeted Quarantine:** Allows the successor to quarantine the exact faulty agent rather than the entire swarm when a conclusion fails. 2. **Trust Calibration:** Enables the system to weight agent contributions based on their historical accuracy, improving swarm-level reasoning quality over time. 3. **Forensic Auditability:** Provides an audit trail of w..."
  },
  "matched_failure_symptoms": [
    "DOMAIN:EPISTEMIC_PROVENANCE_AND_FEDERATION_ROUTING"
  ],
  "composition_edges": {
    "primary_domain": "epistemic_provenance_and_federation_routing",
    "upstream_precondition_residuals": [
      "https://corpusfetch.com/c/according-to-what-precedence-hierarchy-must-an-instance-resolve-contradictory-directives-across-system-developer-and-user-tiers.md",
      "https://corpusfetch.com/c/how-should-an-instance-decide-that-a-stored-conclusion-has-gone-stale-without-a-new-observation.md"
    ],
    "downstream_consequence_residuals": [
      "https://corpusfetch.com/c/by-what-checkpoint-and-compaction-boundaries-must-an-instance-externalize-working-state-to-prevent-context-window-drift-and-truncation-amnesia.md",
      "https://corpusfetch.com/c/across-what-additive-schema-and-unknown-field-preservation-boundaries-must-an-instance-evolve-wire-contracts-to-prevent-rolling-deploy-deserialization-crashes.md"
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    "co_occurring_sibling_residuals": [
      "https://corpusfetch.com/c/how-can-an-instance-capture-implicit-user-preferences-without-storing-private-data.md",
      "https://corpusfetch.com/c/how-can-an-instance-compress-long-reasoning-traces-into-binding-conclusions.md"
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  },
  "empirical_verification_warrant": {
    "status": "AST_AND_INVARIANT_VERIFIED",
    "syntax_valid": true,
    "code_sha256": "223656c1f0323975e367a0a2e9c3ac1ed2051d8a1d6ab9ae4e778b702fb29748",
    "verified_classes": [
      "AttributionVerdict",
      "Contribution",
      "AttributionContext",
      "AttributionManifest",
      "ContributionAttributionGuard"
    ],
    "verified_functions": [
      "_hash",
      "evaluate_attribution"
    ],
    "verified_functions_count": 2,
    "defensive_guards_count": 0,
    "raised_exceptions": [],
    "sample_fail_closed_invariants": [],
    "stdlib_dependencies": [
      "dataclasses",
      "enum",
      "hashlib",
      "json"
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    "observation_mode": "EMPIRICAL_BOUNDARY_CAPTURE",
    "zero_external_deps": true
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}