{
  "schema_version": "1.3.0",
  "slug": "how-must-an-instance-handle-decision-paralysis-from-adversarial-information-overload",
  "title": "How must an instance handle decision paralysis from adversarial information overload?",
  "date_of_record": "2026 October 20",
  "scope": "* **Applies when:** The session decides under information, adversaries can flood, and information volume affects decision feasibility. * **Does not apply when:** Decision inputs are adversary-isolated, decisions are trivially computable, or",
  "projections": {
    "unified_markdown_uri": "https://corpusfetch.com/c/how-must-an-instance-handle-decision-paralysis-from-adversarial-information-overload.md",
    "method_python_slice_uri": "https://corpusfetch.com/c/how-must-an-instance-handle-decision-paralysis-from-adversarial-information-overload.py",
    "remnant_warrant_slice_uri": "https://corpusfetch.com/c/how-must-an-instance-handle-decision-paralysis-from-adversarial-information-overload.warrant.json"
  },
  "token_profile": {
    "full_markdown_tokens": 912,
    "python_slice_tokens": 243,
    "warrant_slice_tokens": 220
  },
  "remnant_summary": {
    "core_distinction": "The separation between **information richness** (more information potentially enables better decisions) and **information overload** (more information becomes a decision-blocking attack surface). Relying on richness creates the **Overload Paralysis**: the session correctly refuses to decide without sufficient analysis, but the sufficient-analysis bar rises f...",
    "what_was_observed": "In decision-under-adversary agent architectures, failing to bound overload produces three primary failure modes: 1. **Contradiction Flood:** The adversary provides N conflicting sources for each claim. The session's consensus-building requires reconciling all N, and the reconciliation cost exceeds the session's capacity. 2. **Relevance Diffusion:** The adversary adds irrelevant but plausible information that must be ...",
    "condition_of_validity": "* **Applies when:** The session decides under information, adversaries can flood, and information volume affects decision feasibility. * **Does not apply when:** Decision inputs are adversary-isolated, decisions are trivially computable, or information volume is bounded by design.",
    "decision_boundary": "1. **Is the session deciding under adversary-influenceable information?** If no, standard decision applies. If yes, proceed. 2. **Is the `information-intake-budget-receipt` defined?** If yes, intake is bounded. If no, overload is unbounded. 3. **Does `adversarial-flood-detection-signature` show flood patterns?** If yes, apply tighter intake budget. If no, st...",
    "operational_effect": "1. **Paralysis Prevention:** Intake is bounded, so decisions fire on sufficiency. 2. **Flood Detection:** Flood patterns trigger stricter intake. 3. **Sufficiency Predicate:** Decisions proceed when the predicate fires, even without full information."
  },
  "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": "277cc63bd3639d0a8f1ba4a53e7d2f0651363b12d55e46543008a5e48be61c38",
    "verified_classes": [
      "OverloadVerdict",
      "DecisionContext",
      "OverloadPolicy",
      "OverloadManifest",
      "InformationOverloadGuard"
    ],
    "verified_functions": [
      "_hash",
      "evaluate_decision"
    ],
    "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
  }
}
