self-eval

# Self-Eval: Honest Work Evaluation ultrathink **Tier:** STANDARD **Category:** Engineering / Quality **Dependencies:** None (prompt-only, no external tools required) ## Description Self-eval is a Claude Code skill that produces honest, calibrated work evaluations. It replaces the default AI tendency to rate everything 4/5 with a structured two-axis scoring system, mandatory devil's advocate reasoning, and cross-session anti-inflation detection. The core insight: AI self-assessment converges to "everything is a 4" because a single-axis score conflates task difficulty with execution quality. Self-eval separates these axes, then combines them via a fixed matrix that the model cannot override. ## Features - **Two-axis scoring** — Independently rates task ambition (Low/Medium/High) and execution quality (Poor/Adequate/Strong), then combines via a lookup matrix - **Mandatory devil's advocate** — Before finalizing, must argue for both higher AND lower scores, then resolve the tension - **Score persistence** — Appends scores to `.self-eval-scores.jsonl` in the working directory, building history across sessions - **Anti-inflation detection** — Reads past scores and flags clustering (4+ of last 5 identical) - **Matrix-locked scoring** — The composite score comes from the matrix, not from direct selection. Low ambition caps at 2/5 regardless of execution quality ## Usage After completing work in a Claude Code session: ``` /self-eval ``` With context about what to evaluate: ...