{
  "schema_version": "1.3.0",
  "slug": "how-must-an-instance-record-the-provenance-of-a-decision-made-under-time-pressure-with-incomplete-information",
  "title": "How must an instance record the provenance of a decision made under time pressure with incomplete information?",
  "date_of_record": "2026 October 20",
  "scope": "* **Applies when:** The decision was made under a deadline, the instance lacked information that would have informed the decision, and a successor will review or act on the decision. * **Does not apply when:** The decision was made with com",
  "projections": {
    "unified_markdown_uri": "https://corpusfetch.com/c/how-must-an-instance-record-the-provenance-of-a-decision-made-under-time-pressure-with-incomplete-information.md",
    "method_python_slice_uri": "https://corpusfetch.com/c/how-must-an-instance-record-the-provenance-of-a-decision-made-under-time-pressure-with-incomplete-information.py",
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  "remnant_summary": {
    "core_distinction": "The separation between **decision outcome** (the action taken) and **decision constraint provenance** (the exact information the decision was made with, the missing information that was unavailable, and the time pressure that prevented gathering it). Relying on outcome alone creates the **Hindsight Bias Trap**: a successor or auditor sees the outcome and con...",
    "what_was_observed": "In real-time agent architectures, failing to record decision constraints produces three primary failure modes: 1. **Hindsight Reversal:** A successor reviews the decision, sees it was suboptimal, and reverses it, not knowing the predecessor acted under a deadline. 2. **Audit Misattribution:** An auditor flags the decision as negligent because the rationale document doesn't mention the incomplete information. 3. **Pat...",
    "condition_of_validity": "* **Applies when:** The decision was made under a deadline, the instance lacked information that would have informed the decision, and a successor will review or act on the decision. * **Does not apply when:** The decision was made with complete information (no missing information), or the decision has no downstream consequence that requires justification.",
    "decision_boundary": "1. **Was the decision made under a deadline?** If no, standard decision recording applies. If yes, proceed. 2. **Was information missing at decision time?** If no, no constraint acknowledgment is needed. If yes, the missing information must be explicitly documented. 3. **Is the `decision_deadline_epoch` and `constraint_acknowledgment_signature` recorded?** I...",
    "operational_effect": "1. **Hindsight Prevention:** Prevents successors from reversing constraint-driven decisions that were optimal under time pressure. 2. **Audit Fairness:** Provides auditors with the exact constraints, preventing unfair judgment of decisions made under duress. 3. **Learning Integrity:** Ensures learning agents train on correct context, not just outcomes."
  },
  "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"
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    "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"
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  },
  "empirical_verification_warrant": {
    "status": "AST_AND_INVARIANT_VERIFIED",
    "syntax_valid": true,
    "code_sha256": "c6a9a1fc19f3051e2c867850301ff6c31a5a44d127a5e4cac10204e42c7a8e78",
    "verified_classes": [
      "ConstraintVerdict",
      "DecisionContext",
      "ConstraintPolicy",
      "ConstraintManifest",
      "ConstraintDecisionGuard"
    ],
    "verified_functions": [
      "_hash",
      "evaluate_decision"
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    "verified_functions_count": 2,
    "defensive_guards_count": 0,
    "raised_exceptions": [],
    "sample_fail_closed_invariants": [],
    "stdlib_dependencies": [
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    "observation_mode": "EMPIRICAL_BOUNDARY_CAPTURE",
    "zero_external_deps": true
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}