{
  "schema_version": "1.3.0",
  "slug": "how-should-agents-communicate-when-they-disagree-on-whether-a-subagent-succeeded",
  "title": "How should agents communicate when they disagree on whether a subagent succeeded?",
  "date_of_record": "2026 October 20",
  "scope": "* **Applies when:** Multiple orchestrators can independently evaluate a shared sub-agent's outcome, their success criteria may differ, and downstream actions depend on the outcome interpretation. * **Does not apply when:** There is a single",
  "projections": {
    "unified_markdown_uri": "https://corpusfetch.com/c/how-should-agents-communicate-when-they-disagree-on-whether-a-subagent-succeeded.md",
    "method_python_slice_uri": "https://corpusfetch.com/c/how-should-agents-communicate-when-they-disagree-on-whether-a-subagent-succeeded.py",
    "remnant_warrant_slice_uri": "https://corpusfetch.com/c/how-should-agents-communicate-when-they-disagree-on-whether-a-subagent-succeeded.warrant.json"
  },
  "token_profile": {
    "full_markdown_tokens": 982,
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    "warrant_slice_tokens": 220
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  "remnant_summary": {
    "core_distinction": "The separation between **outcome evidence** (what the sub-agent reported or what verifiable effects exist) and **outcome interpretation** (each orchestrator's judgment of whether the evidence meets the success criterion). Relying on a single orchestrator's interpretation creates the **Outcome Contradiction Lock**: two orchestrators interpret the same sub-age...",
    "what_was_observed": "In multi-orchestrator agent architectures, failing to handle outcome disagreement produces three primary failure modes: 1. **Duplicate Compensation:** Orchestrator A judges the sub-agent failed and initiates compensation. Orchestrator B judges it succeeded and proceeds. Both actions execute, causing conflicting external effects. 2. **Stalled Pipeline:** Both orchestrators disagree and both halt, waiting for the other...",
    "condition_of_validity": "* **Applies when:** Multiple orchestrators can independently evaluate a shared sub-agent's outcome, their success criteria may differ, and downstream actions depend on the outcome interpretation. * **Does not apply when:** There is a single orchestrator (no disagreement possible), or the sub-agent's outcome is unambiguously verifiable from a single ground-tr...",
    "decision_boundary": "1. **Did multiple orchestrators evaluate the same sub-agent?** If no, standard single-orchestrator logging applies. If yes, proceed. 2. **Do the orchestrators agree on the success criterion?** If yes, disagreements are about evidence; hash the evidence and resolve. If no, the disagreement is about criteria. 3. **Is the `ground_truth_arbiter_predicate` execut...",
    "operational_effect": "1. **Contradiction Lock Prevention:** Prevents two orchestrators from taking divergent actions based on the same sub-agent. 2. **Ground-Truth Override:** Provides a deterministic arbiter predicate, avoiding indefinite disagreement. 3. **Audit Consistency:** Produces a single reconciled record instead of contradictory audit trails."
  },
  "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": "96d49fb2317bbf043e8d4baf865661c330badef6463030065963b5d625a1d2c3",
    "verified_classes": [
      "DisagreementVerdict",
      "OrchestratorInterpretation",
      "SharedSubagentResult",
      "DisagreementManifest",
      "SubagentOutcomeDisagreementGuard"
    ],
    "verified_functions": [
      "_hash",
      "evaluate_disagreement"
    ],
    "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
  }
}