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Repo-local harness for evaluating agents, classifying failures, validating regressions, and producing review artifacts.
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
Use when the user wants the KADE System itself, including Layer 1 and Layer 2 context loading, KADE session structure, HUMAN.md and kade/ overlays, or project initialization and handoff workflows. This packet-owned wrapper is installable into ~/.agents/skills, ~/.codex/skills, and ~/.claude/skills.
Use when the task should consult, capture, validate, evolve, or retire reusable workflow shortcuts through the local `llm-wiki-skills` skill/CLI surface. MCP is optional transport only. This packet-owned wrapper explains the full tool lifecycle in depth and is installable into ~/.agents/skills, ~/.codex/skills, ~/.claude/skills, and ~/.pi/agent/skills.
Use this skill when the repo is an llm-wiki-memory vault and the task is to ingest a source, answer from the persistent wiki, create or review reusable skills, use pk-qmd for repo-local evidence retrieval, consult brv for durable memory, or lint and maintain the wiki.
Use the repo-local harness to benchmark Gym-Anything-compatible agents, cluster failures, and generate human-gated improvement proposals.
Run the repo-local harness to evaluate agents, classify failures, propose human-gated improvements, validate regressions, and generate review packets.
Use when the user wants the KADE plus gstack bridge, including session kickoff with user-profile context, /g-kade install style project scaffolding, repo adaptation, or structured handoff logging tied to llm-wiki-memory packet setup. This packet-owned wrapper is installable into ~/.agents/skills, ~/.codex/skills, and ~/.claude/skills.
| name | agent-self-improvement |
| description | Repo-local harness for evaluating agents, classifying failures, validating regressions, and producing review artifacts. |
Run:
python .agent-improvement\scripts\repo_local_harness.py all --config agent-improvement.config.json