← ClaudeAtlas

agent-self-evaluationlisted

Use after completing any non-trivial task. The agent self-rates its output on 5 axes — accuracy, completeness, clarity, actionability, conciseness — with concrete evidence per criterion. Produces a structured 1-5 scorecard with specific improvement suggestions.
SkotAlexsander/skills · ★ 1 · AI & Automation · score 75
Install: claude install-skill SkotAlexsander/skills
# Agent Self-Evaluation After completing a complex task, the agent pauses to rate its own output against a structured 5-axis rubric. This is NOT a pass/fail gate — it's a deliberate reflection step that catches omissions, flags overconfidence, and surface areas for improvement before the user has to. ## When to Activate - After writing code that spans 3+ files or 50+ lines - After completing a multi-step workflow (implement → test → review) - After a debugging session that involved 3+ attempts - After producing a design document, architecture decision, or written analysis - When the user asks "how good was that?" or "rate yourself" - At the end of any session Stop hook (if configured — see `references/hook-integration.md`) ## Core Concepts ### The 5 Evaluation Axes | Axis | Question | What it catches | |---|---|---| | **Accuracy** | Are the facts, claims, and outputs correct? | Hallucinations, wrong API names, incorrect syntax, false statements | | **Completeness** | Did it cover everything the user asked for? | Missed edge cases, unhandled error paths, forgotten requirements, skipped subtasks | | **Clarity** | Is the explanation understandable and well-structured? | Confusing explanations, jargon without definition, missing context, rambling | | **Actionability** | Can the user act on the output immediately? | Vague suggestions, missing steps, "you should X" without showing how, no verification path | | **Conciseness** | Did it use the minimum words/tokens needed? | Re