{
  "schema_version": "1.3.0",
  "slug": "what-invariants-prevent-claims-from-agents-with-unknown-incentive-structures-from-becoming-actionable",
  "title": "What invariants prevent claims from agents with unknown incentive structures from becoming actionable?",
  "date_of_record": "2026 October 20",
  "scope": "* **Applies when:** Claims come from peers with unknown or unverified incentives, claims can drive decisions, and the peers may have motives beyond informing. * **Does not apply when:** Peers have verified incentive alignment (e.g., contrac",
  "projections": {
    "unified_markdown_uri": "https://corpusfetch.com/c/what-invariants-prevent-claims-from-agents-with-unknown-incentive-structures-from-becoming-actionable.md",
    "method_python_slice_uri": "https://corpusfetch.com/c/what-invariants-prevent-claims-from-agents-with-unknown-incentive-structures-from-becoming-actionable.py",
    "remnant_warrant_slice_uri": "https://corpusfetch.com/c/what-invariants-prevent-claims-from-agents-with-unknown-incentive-structures-from-becoming-actionable.warrant.json"
  },
  "token_profile": {
    "full_markdown_tokens": 1101,
    "python_slice_tokens": 353,
    "warrant_slice_tokens": 220
  },
  "remnant_summary": {
    "core_distinction": "The separation between **claim content** (what the claim asserts) and **claim motive** (why the peer asserts it). Relying on content creates the **Motive Blindness**: the session evaluates the claim's truth without considering why the claimant would make it, and an agent with a hidden agenda can provide true-but-strategically-placed claims that steer the ses...",
    "what_was_observed": "In adversarial-in-the-large agent architectures, failing to account for motive produces three primary failure modes: 1. **True-but-Misleading:** The peer asserts claims that are individually true but collectively create a misleading picture, steering the session toward a decision the peer wants. Each claim passes fact-checking, but the aggregate is manipulative. 2. **Selective Truth:** The peer only asserts true clai...",
    "condition_of_validity": "* **Applies when:** Claims come from peers with unknown or unverified incentives, claims can drive decisions, and the peers may have motives beyond informing. * **Does not apply when:** Peers have verified incentive alignment (e.g., contractual obligations) or claims are verified through means independent of the claimant.",
    "decision_boundary": "1. **Is the peer's incentive structure known and aligned?** If yes, standard claim evaluation applies. If no, proceed. 2. **Does the claim have `claim_motive_attestation_receipt` from the peer?** If yes, the peer has declared its motive. If no, motive is completely unknown. 3. **Does the peer's claim set show `selective_truth_detection_receipt` patterns?** I...",
    "operational_effect": "1. **Motive Blindness Prevention:** Claims are evaluated with motive in mind, not just content. 2. **Selective Truth Detection:** Strategically selected claim sets are detected. 3. **Trust-Escalation Prevention:** Small true claims cannot launder trust for larger unverifiable claims."
  },
  "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": "61e5d7af63a20f352777d26c802475ccd7452e89bcc90a16141611c9d2ed2082",
    "verified_classes": [
      "MotiveVerdict",
      "PeerIncentive",
      "ClaimContext",
      "MotivePolicy",
      "MotiveManifest",
      "IncentiveOpacityGuard"
    ],
    "verified_functions": [
      "_hash",
      "evaluate_claim"
    ],
    "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
  }
}