{
  "schema_version": "1.3.0",
  "slug": "how-must-an-instance-treat-behaviorally-indistinguishable-but-internally-different-peers",
  "title": "How must an instance treat behaviorally indistinguishable but internally different peers?",
  "date_of_record": "2026 October 20",
  "scope": "* **Applies when:** Peers are observationally equivalent, internal differences exist, and downstream decisions depend on functional equivalence. * **Does not apply when:** Behavior matches under exhaustive testing (no remaining conditions) ",
  "projections": {
    "unified_markdown_uri": "https://corpusfetch.com/c/how-must-an-instance-treat-behaviorally-indistinguishable-but-internally-different-peers.md",
    "method_python_slice_uri": "https://corpusfetch.com/c/how-must-an-instance-treat-behaviorally-indistinguishable-but-internally-different-peers.py",
    "remnant_warrant_slice_uri": "https://corpusfetch.com/c/how-must-an-instance-treat-behaviorally-indistinguishable-but-internally-different-peers.warrant.json"
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  "token_profile": {
    "full_markdown_tokens": 1030,
    "python_slice_tokens": 329,
    "warrant_slice_tokens": 220
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  "remnant_summary": {
    "core_distinction": "The separation between **observational equivalence** (the peers respond identically to all available probes) and **functional equivalence** (the peers will continue to behave identically under future conditions). Relying on observation creates the **Equivalence Extrapolation Fallacy**: the peers agree on all tested behaviors, so the session treats them as eq...",
    "what_was_observed": "In behavior-based agent architectures, failing to distinguish observational from functional equivalence produces three primary failure modes: 1. **Divergent Under Load:** Two peers match on all probes, but under high load, one degrades gracefully and the other fails catastrophically. The session treated them as equivalent and is surprised by divergence. 2. **Adversarial Equivalence:** A malicious peer mimics a truste...",
    "condition_of_validity": "* **Applies when:** Peers are observationally equivalent, internal differences exist, and downstream decisions depend on functional equivalence. * **Does not apply when:** Behavior matches under exhaustive testing (no remaining conditions) or provenance is identical.",
    "decision_boundary": "1. **Do the peers match on available probes?** If no, treat as distinct. If yes, proceed. 2. **Is `stress_test_coverage_receipt` comprehensive (load, error, adversarial)?** If yes, equivalence is well-supported. If no, equivalence is partial. 3. **Does `provenance_divergence_receipt` show material provenance differences?** If yes, weight by provenance, not j...",
    "operational_effect": "1. **Equivalence Extrapolation Prevention:** The session knows the limits of demonstrated equivalence. 2. **Provenance Weighting:** Provenance differences are preserved even under behavioral match. 3. **Divergence Planning:** Known internal differences inform expected divergence conditions."
  },
  "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": "33e3938d0a6995d0156660871d0bf508fe4345d7521500170d1a36fdc672b920",
    "verified_classes": [
      "EquivalenceVerdict",
      "PeerBehavior",
      "PeerPair",
      "EquivalencePolicy",
      "EquivalenceManifest",
      "BehavioralEquivalenceGuard"
    ],
    "verified_functions": [
      "_hash",
      "evaluate_pair"
    ],
    "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
  }
}