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생산성 및 협업 · SKILL.md

bridge_recovery_harness

bridge_recovery_harness

Run a bounded BridgeStan score-model proxy recovery that invokes generated module scripts, logs command evidence, and writes validator-ready recovery artifacts.

Independent GitHub snapshot · Automated classification · Original documentation governs

Skill 문서

GitHub

name: bridge_recovery_harness description: Run a bounded BridgeStan score-model proxy recovery that invokes generated module scripts, logs command evidence, and writes validator-ready recovery artifacts.

Bridge Recovery Harness

Use this skill when a soft-mode recovery must prove BridgeStan-like score-model behavior without compiling the full BridgeStan stack. It coordinates the other generated skills and produces auditable recovery artifacts.

Inputs

  • Attempt directory.
  • Generated skills root.
  • module_plan.json fast recovery target.
  • environment/runtime_handoff.json.

Outputs

  • recovery/recovery_result.json.
  • recovery/source_manifest.json.
  • recovery/logs/experiment_command_log.json.
  • recovery/logs/generated_skill_invocations.json.
  • Data, contract, transform, and score logs used by the proxy.

Workflow

  1. Confirm the runtime handoff recommends reduced/proxy recovery or that full BridgeStan runtime is unavailable.
  2. Create a tiny Bernoulli Stan source and observation data inside the current attempt.
  3. Call the generated contract, transform, and score scripts through subprocesses.
  4. Compute a mechanism-check pass-rate metric from the generated outputs.
  5. Write source manifest entries limited to allowed recovery sources.
  6. Run the Distiller recovery validator after the harness completes.

Validation

Run python tests/test_bridge_recovery_harness.py from this skill directory for a command-free smoke check of metric aggregation.

Limitations

This harness is a declared proxy. It must not claim that the real BridgeStan package or compiled Stan shared object ran unless environment evidence proves that separately.

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