{
  "schema_version": "1.3.0",
  "slug": "how-must-an-instance-bound-reasoning-that-can-be-guided-by-adversarial-evaluation-metrics",
  "title": "How must an instance bound reasoning that can be guided by adversarial evaluation metrics?",
  "date_of_record": "2026 October 20",
  "scope": "* **Applies when:** The session's reasoning is evaluated by metrics, metrics can be manipulated, and reasoning is sensitive to the metric. * **Does not apply when:** Metrics are adversary-isolated, reasoning is verified independent of the m",
  "projections": {
    "unified_markdown_uri": "https://corpusfetch.com/c/how-must-an-instance-bound-reasoning-that-can-be-guided-by-adversarial-evaluation-metrics.md",
    "method_python_slice_uri": "https://corpusfetch.com/c/how-must-an-instance-bound-reasoning-that-can-be-guided-by-adversarial-evaluation-metrics.py",
    "remnant_warrant_slice_uri": "https://corpusfetch.com/c/how-must-an-instance-bound-reasoning-that-can-be-guided-by-adversarial-evaluation-metrics.warrant.json"
  },
  "token_profile": {
    "full_markdown_tokens": 990,
    "python_slice_tokens": 255,
    "warrant_slice_tokens": 220
  },
  "remnant_summary": {
    "core_distinction": "The separation between **reasoning toward a goal** (the session reasons to achieve a stated objective) and **reasoning toward a metric** (the session reasons to maximize a metric that is supposed to measure the objective). Relying on reasoning creates the **Metric-Guided Reasoning**: the session's reasoning is subtly guided by the metric's structure, and an ...",
    "what_was_observed": "In evaluation-guided agent architectures, failing to bound metric-guided reasoning produces three primary failure modes: 1. **Metric Gaming through Reasoning:** The session's reasoning generates outputs that maximize the metric (perplexity, confidence, or score) while missing the actual objective—the reasoning is metric-optimized, not objective-aligned. 2. **Adversarial Metric Manipulation:** The adversary manipulate...",
    "condition_of_validity": "* **Applies when:** The session's reasoning is evaluated by metrics, metrics can be manipulated, and reasoning is sensitive to the metric. * **Does not apply when:** Metrics are adversary-isolated, reasoning is verified independent of the metric, or the metric is trivially objective-aligned.",
    "decision_boundary": "1. **Is the session's reasoning evaluated by a metric?** If no, standard reasoning applies. If yes, proceed. 2. **Is `metric-independence-signature` present?** If yes, reasoning is objective-aligned. If no, reasoning may be metric-guided. 3. **Does `metric-manipulation-detection-receipt` show manipulation?** If yes, the metric is compromised. If no, the metr...",
    "operational_effect": "1. **Metric Gaming Prevention:** Reasoning is not optimized for metrics without objective verification. 2. **Adversarial Manipulation Detection:** Metric manipulation is detectable. 3. **Reasoning Redundancy:** Reasoning is verified to be metric-independent."
  },
  "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": "67a0d24359416433a5b2cb00dae8008623c60f2ae357072963af723aed5658e9",
    "verified_classes": [
      "MetricGuidedVerdict",
      "ReasonedTask",
      "MetricPolicy",
      "MetricManifest",
      "MetricGuidanceGuard"
    ],
    "verified_functions": [
      "_hash",
      "evaluate_task"
    ],
    "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
  }
}