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Read-only report of improvement suggestions from eval-core analysis engine
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
Pre-action boundary checking — validates agent tool calls against declared capabilities and task contracts
Auto-detect project context and optimize harness — deactivate unused agents/skills, suggest missing experts, generate project profile
Multi-LLM adversarial consensus loop — 3+ LLMs compete to find flaws in designs/specs until unanimous agreement is reached
Monitor Claude Code releases and auto-generate GitHub issues for each new version
Execute OpenAI Codex CLI prompts and return results
YAML-based DAG workflow engine with topological execution and failure strategies
| name | omcustomcodex:improve-report |
| description | Read-only report of improvement suggestions from eval-core analysis engine |
| scope | harness |
| user-invocable | true |
Display improvement suggestions from eval-core analysis engine as read-only report. No file modifications, no GitHub mutations.
Surface actionable improvement suggestions gathered by the eval-core analysis engine. Reads from eval-core's local database and renders insights as structured markdown. Useful for understanding routing quality, skill effectiveness, and agent usage patterns.
/omcustomcodex:improve-report
command -v eval-core 2>/dev/null || ls node_modules/.bin/eval-core 2>/dev/null
If not found → skip to Step 4 (fallback).
eval-core analyze --format markdown
Count sessions recorded from the output metadata:
| Sessions recorded | Confidence | Behavior |
|---|---|---|
| < 5 | [confidence: low] | Show results with message: "최소 5세션 이상의 데이터가 필요합니다. 현재 데이터로도 초기 분석은 가능하지만, 정확도는 제한적입니다." |
| 5–20 | [confidence: medium] | Show results with medium confidence note |
| > 20 | [confidence: high] | Show results normally |
If output contains data → display as structured markdown with confidence annotation prepended.
If command not found OR output is empty:
[omcodex:improve-report] 데이터 없음
eval-core가 설치되어 있지 않거나 아직 충분한 세션 데이터가 수집되지 않았습니다.
eval-core를 설치하거나 더 많은 세션을 진행한 후 다시 실행하세요.