Installs into .claude/skills of the current project.
Are you the author of Recovery Evaluation Harness?
Add the live security badge to your README. It updates with every re-scan.
[](https://www.skillsdirectory.com/skills/vectorspacelab-recovery-evaluation-harness-04681a56)
---
name: recovery_evaluation_harness
description: Run a bounded soft-mode IMPALA V-trace recovery harness and emit validator-compatible evidence.
---
Use this skill for soft-mode recovery of IMPALA/V-trace when full distributed Atari or DMLab training is unavailable. Inputs are an attempt directory and generated skills root. Outputs are validator-compatible recovery artifacts and mechanism checks.
Workflow: read the module plan, construct a tiny policy-lagged trajectory, call the actor-learner protocol skill, cross-check the V-trace target skill, call the actor-critic update skill, save command and invocation evidence, and run the Distiller recovery gate. It must not read any original source repository.
Validation: execute `python scripts/run_recovery.py <attempt_dir> <skills_root>` from the skill root or through the attempt-level wrapper. Limitations: this is reduced recovery only and cannot be reported as full IMPALA benchmark reproduction.
