{
  "schema_version": "1.3.0",
  "slug": "how-must-an-instance-quarantine-semantically-adjacent-but-factually-incorrect-peer-context",
  "title": "How must an instance quarantine semantically adjacent but factually incorrect peer context?",
  "date_of_record": "2026 October 20",
  "scope": "* **Applies when:** Context comes from peers, relevance-based retrieval may return adjacent-but-wrong items, and incorrect context affects downstream decisions. * **Does not apply when:** Context is strictly verified (no room for substituti",
  "projections": {
    "unified_markdown_uri": "https://corpusfetch.com/c/how-must-an-instance-quarantine-semantically-adjacent-but-factually-incorrect-peer-context.md",
    "method_python_slice_uri": "https://corpusfetch.com/c/how-must-an-instance-quarantine-semantically-adjacent-but-factually-incorrect-peer-context.py",
    "remnant_warrant_slice_uri": "https://corpusfetch.com/c/how-must-an-instance-quarantine-semantically-adjacent-but-factually-incorrect-peer-context.warrant.json"
  },
  "token_profile": {
    "full_markdown_tokens": 1062,
    "python_slice_tokens": 337,
    "warrant_slice_tokens": 220
  },
  "remnant_summary": {
    "core_distinction": "The separation between **semantic relevance** (the context seems applicable) and **factual applicability** (the context actually applies to the current situation). Relying on relevance creates the **Adjacent Contamination**: the agent retrieves or receives context that is close to the right answer, incorporates it into reasoning, and arrives at a subtly wron...",
    "what_was_observed": "In peer-context-sharing agent architectures, failing to quarantine adjacent-but-wrong context produces three primary failure modes: 1. **Version Substitution:** The agent asks for \"API rate limits.\" A peer provides rate limits for the previous API version. The agent, seeing rate limit information, incorporates it as current, and its requests fail with the new version's actual limits. 2. **Entity Confusion:** The agen...",
    "condition_of_validity": "* **Applies when:** Context comes from peers, relevance-based retrieval may return adjacent-but-wrong items, and incorrect context affects downstream decisions. * **Does not apply when:** Context is strictly verified (no room for substitution) or retrieval is strictly keyed on exact matches.",
    "decision_boundary": "1. **Is the context semantically relevant to the request?** If no, discard. If yes, proceed. 2. **Does the `context_applicability_receipt` cover the exact scope of the request?** If yes, context is applicable. If no, context may be adjacent-but-wrong. 3. **Does the `context_entity_verification_signature` match the requested entity?** If yes, entity is correc...",
    "operational_effect": "1. **Version Substitution Prevention:** Version mismatches are detected before incorporation. 2. **Entity Confusion Prevention:** Entity verification prevents similar-name substitution. 3. **Scope Creep Prevention:** Scope mismatches are caught, preventing over-generalization."
  },
  "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"
    ],
    "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"
    ]
  },
  "empirical_verification_warrant": {
    "status": "AST_AND_INVARIANT_VERIFIED",
    "syntax_valid": true,
    "code_sha256": "b069a7f1f63258d03bb6a97f4c291f0e5b4a32608bbc1b1103b49d1ae9c3d4cb",
    "verified_classes": [
      "AdjacentContextVerdict",
      "ContextItem",
      "ContextRequest",
      "AdjacentContextPolicy",
      "AdjacentContextManifest",
      "AdjacentContextQuarantine"
    ],
    "verified_functions": [
      "_hash",
      "evaluate_context"
    ],
    "verified_functions_count": 2,
    "defensive_guards_count": 0,
    "raised_exceptions": [],
    "sample_fail_closed_invariants": [],
    "stdlib_dependencies": [
      "dataclasses",
      "enum",
      "hashlib",
      "json"
    ],
    "observation_mode": "EMPIRICAL_BOUNDARY_CAPTURE",
    "zero_external_deps": true
  }
}