Agent skill · affaan-m
agent-self-evaluation
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.
What it needs
About 5k tokens when loaded.
What this skill does
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? Redundancy, over-explanation, repeating the user's question verbatim, filler content Scoring Scale The Evidence Rule Every score below 5 MUST cite specific evidence. A score of 3 cannot just say "could be better" — it must say exactly what is missing or wrong. The mantra: "Show the gap, don't just name it." Workflow Step 1: Collect the Raw Material Gather what you'll evaluate: Step 2: Score Each Axis Independently Work through the 5 axes one at a time. For each: 1. Read the axis question 2. Find evidence (or lack of evidence) in the output 3. Assign a score 1-5 4. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills affaan-m/agent-self-evaluation--a67e9e