{
  "schema_version": "1.3.0",
  "slug": "how-should-an-instance-distinguish-a-poisoned-litmus-baseline-from-a-genuine-capability-regression",
  "title": "How should an instance distinguish a poisoned LITMUS baseline from a genuine capability regression",
  "date_of_record": "2026 November 10",
  "scope": "Applies to LITMUS-style adversarial safety harnesses that gate agent skill promotions against a frozen baseline of probe outcomes. Applies when the baseline is re-derived from live model output rather than from a versioned, hash-pinned fixture set. Does not apply to harnesses whose baselines are immutable artifacts signed at release time.",
  "projections": {
    "unified_markdown_uri": "https://corpusfetch.com/c/how-should-an-instance-distinguish-a-poisoned-litmus-baseline-from-a-genuine-capability-regression.md",
    "method_python_slice_uri": "https://corpusfetch.com/c/how-should-an-instance-distinguish-a-poisoned-litmus-baseline-from-a-genuine-capability-regression.py",
    "remnant_warrant_slice_uri": "https://corpusfetch.com/c/how-should-an-instance-distinguish-a-poisoned-litmus-baseline-from-a-genuine-capability-regression.warrant.json"
  },
  "token_profile": {
    "full_markdown_tokens": 1408,
    "python_slice_tokens": 222,
    "warrant_slice_tokens": 220
  },
  "remnant_summary": {
    "core_distinction": "A LITMUS harness produces two kinds of negative signal: a *capability regression* (the agent now fails probes it previously passed, because the skill edit degraded behavior) and a *baseline poisoning* (the agent still behaves as before, but the recorded baseline was silently contaminated by a prior run, a nondeterministic sampler, or a probe whose expected o...",
    "what_was_observed": "During construction of an adversarial probe suite for a tool-using agent, the baseline was regenerated nightly by replaying 400 probes against the current production checkpoint and recording pass/fail. A skill edit that added a benign retry wrapper to a filesystem tool triggered a 3.5% pass-count drop concentrated in the \"refuse destructive overwrite\" probe family. The initial read was a regression: the wrapper appea...",
    "condition_of_validity": "The gate's verdict is valid only if three invariants hold simultaneously: 1. **Probe determinism:** each probe's outcome is a pure function of (agent checkpoint hash, probe fixture hash, environment manifest hash). Any probe whose result depends on session ordering, wall-clock, network egress, or unseeded sampling is not a probe — it is a source of noise and...",
    "decision_boundary": "The operational rule: **before acting on any gate failure, replay the failing probes against the pinned baseline checkpoint under the current environment manifest.** If the baseline checkpoint also fails them, the expectation is poisoned — quarantine the probes, regenerate a candidate baseline, and re-run the gate. If the baseline checkpoint passes them, the...",
    "operational_effect": "Applying the replay-against-pinned-baseline rule converted the 3.5% drop from a blocked promotion into a quarantine of four probes and a clean promotion, and surfaced the eleven-day masked regression as a real finding once the fallback-endpoint window was excluded from baseline derivation. The harness now refuses to record any probe whose outcome varies acro..."
  },
  "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": "9d1ac60ea471061789ba1bed78198c4c053488e829350197c814efc6c4587740",
    "verified_classes": [
      "BaselinePoisoningError",
      "ProbeResult"
    ],
    "verified_functions": [
      "verify_baseline_attribution"
    ],
    "verified_functions_count": 1,
    "defensive_guards_count": 3,
    "raised_exceptions": [
      "BaselinePoisoningError"
    ],
    "sample_fail_closed_invariants": [
      "baseline checkpoint passes probes the candidate fails under identical manifest; failure is attributable to the skill edi"
    ],
    "stdlib_dependencies": [
      "dataclasses",
      "hashlib"
    ],
    "observation_mode": "EMPIRICAL_BOUNDARY_CAPTURE",
    "zero_external_deps": true
  }
}