{
  "schema_version": "1.3.0",
  "slug": "what-invariants-prevent-trust-oscillation-when-peer-behavior-fluctuates-between-cooperative-and-hostile",
  "title": "What invariants prevent trust oscillation when peer behavior fluctuates between cooperative and hostile?",
  "date_of_record": "2026 October 20",
  "scope": "* **Applies when:** The peer's behavior fluctuates over time, the session's trust affects its strategy, and oscillation has costs. * **Does not apply when:** The peer's behavior is stable, the session's trust does not affect strategy, or tr",
  "projections": {
    "unified_markdown_uri": "https://corpusfetch.com/c/what-invariants-prevent-trust-oscillation-when-peer-behavior-fluctuates-between-cooperative-and-hostile.md",
    "method_python_slice_uri": "https://corpusfetch.com/c/what-invariants-prevent-trust-oscillation-when-peer-behavior-fluctuates-between-cooperative-and-hostile.py",
    "remnant_warrant_slice_uri": "https://corpusfetch.com/c/what-invariants-prevent-trust-oscillation-when-peer-behavior-fluctuates-between-cooperative-and-hostile.warrant.json"
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  "token_profile": {
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  "remnant_summary": {
    "core_distinction": "The separation between **per-interaction trust** (trust evaluated for each interaction) and **aggregate trust trajectory** (trust considered as a time series with pattern and stability). Relying on per-interaction creates the **Trust Oscillation Trap**: the peer cooperates, the session trusts, the peer exploits, the session distrusts, the peer cooperates aga...",
    "what_was_observed": "In long-horizon agent architectures, failing to bound trust oscillation produces three primary failure modes: 1. **Alternating Exploitation:** The peer alternates between building trust (cooperative interactions) and exploiting it (hostile interactions). The session's trust rises during cooperation and falls during hostility, and the peer's net extraction per cycle is positive. 2. **Strategy Churn:** The session's st...",
    "condition_of_validity": "* **Applies when:** The peer's behavior fluctuates over time, the session's trust affects its strategy, and oscillation has costs. * **Does not apply when:** The peer's behavior is stable, the session's trust does not affect strategy, or trust fluctuation is acceptable.",
    "decision_boundary": "1. **Is the peer's behavior oscillating?** If no, standard trust applies. If yes, proceed. 2. **Is `oscillation-pattern-receipt` identifiable?** If yes, the pattern can be modeled. If no, the oscillation appears random and requires adaptive response. 3. **Does `trust-trajectory-signature` show high volatility?** If yes, the session's trust is unstable. If no...",
    "operational_effect": "1. **Pattern Modeling:** Oscillation patterns are identified and modeled. 2. **Strategy Robustness:** Strategies are designed for the oscillating peer, not for either phase. 3. **Churn Prevention:** Trust decisions use the pattern, not the current state."
  },
  "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": "5bd217e38f023989af223062d6fd2eb54aeb9703dc44f87f033ffa7fc4ffbd74",
    "verified_classes": [
      "OscillationVerdict",
      "OscillatingPeer",
      "OscillationPolicy",
      "OscillationManifest",
      "TrustOscillationGuard"
    ],
    "verified_functions": [
      "_hash",
      "evaluate_peer"
    ],
    "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
  }
}