---
name: "self-eval"
description: "Grade finished work honestly on two axes with a devil's-advocate pass against inflation. Use whenever the user asks how well a task went, to rate the work or for an honest self-review."
license: "MIT"
---
# 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:
```
/self-eval the authentication refactor we just completed
```
The skill reviews the conversation history, identifies what was accomplished, scores it on both axes, runs the devil's advocate check, and appends the result to the score history file.
## Examples
### Example 1: Feature Implementation
```
/self-eval added pagination to the user list API
```
Output:
```
## Self-Evaluation
**Task:** Added cursor-based pagination to the user list API endpoint
**Ambition:** Medium — New feature with established patterns, but required careful backwards compatibility
**Execution:** Strong — All tests pass, handles edge cases, existing clients unaffected
**Devil's Advocate:**
- Lower: Pagination is well-documented. The pattern was copied from another endpoint with minor changes. Could argue Low ambition.
- Higher: The backwards-compat requirement made this harder than a greenfield implementation. Had to support both offset and cursor modes.
- Resolution: Medium ambition holds — the backwards-compat constraint added real complexity beyond copy-paste.
**Score: 4** — Solid execution on meaningful work with real constraints.
```
### Example 2: Bug Fix
```
/self-eval
```
Output:
```
## Self-Evaluation
**Task:** Fixed race condition in the checkout flow causing duplicate orders
**Ambition:** Medium — Required debugging across 3 services to find the root cause
**Execution:** Adequate — Fix works but the test only covers the exact scenario reported, not the general class of race conditions
**Devil's Advocate:**
- Lower: The fix was a single line (adding a mutex). Once found, it was trivial.
- Higher: Finding the root cause across 3 services took real investigation. The mutex placement required understanding the full flow.
- Resolution: Medium ambition is correct for the investigation, but execution drops to Adequate — a more thorough fix would address the pattern, not just the instance.
**Score: 3** — Good debugging work but the fix is narrow.
```
---
## What to Evaluate
$ARGUMENTS
If no arguments provided, review the full conversation history to identify what was accomplished this session. Summarize the work in one sentence before scoring.
## How to Score — Two-Axis Model
Score on two independent axes, then combine using the matrix. Do NOT pick a number first and rationalize it — rate each axis separately, then read the matrix.
### Axis 1: Task Ambition (what was attempted)
Rate the difficulty and risk of what was worked on. NOT how well it was done.
- **Low (1)** — Safe, familiar, routine. No real risk of failure. Examples: minor config changes, simple refactors, copy-paste with small modifications, tasks you were confident you'd complete before starting.
- **Medium (2)** — Meaningful work with novelty or challenge. Partial failure was possible. Examples: new feature implementation, integrating an unfamiliar API, architectural changes, debugging a tricky issue.
- **High (3)** — Ambitious, unfamiliar, or high-stakes. Real risk of complete failure. Examples: building something from scratch in an unfamiliar domain, complex system redesign, performance-critical optimization, shipping to production under pressure.
**Self-check:** If you were confident of success before starting, ambition is Low or Medium, not High.
### Axis 2: Execution Quality (how well it was done)
Rate the quality of the actual output, independent of how ambitious the task was.
- **Poor (1)** — Major failures, incomplete, wrong output, or abandoned mid-task. The deliverable doesn't meet its own stated criteria.
- **Adequate (2)** — Completed but with gaps, shortcuts, or missing rigor. Did the thing but left obvious improvements on the table.
- **Strong (3)** — Well-executed, thorough, quality output. No obvious improvements left undone given the scope.
### Composite Score Matrix
| | Poor Exec (1) | Adequate Exec (2) | Strong Exec (3) |
|------------------------|:---:|:---:|:---:|
| **Low Ambition (1)** | 1 | 2 | 2 |
| **Medium Ambition (2)**| 2 | 3 | 4 |
| **High Ambition (3)** | 2 | 4 | 5 |
**Read the matrix, don't override it.** The composite is your score. The devil's advocate below can cause you to re-rate an axis — but you cannot directly override the matrix result.
Key properties:
- Low ambition caps at 2. Safe work done perfectly is still safe work.
- A 5 requires BOTH high ambition AND strong execution. It should be rare.
- High ambition + poor execution = 2. Bold failure hurts.
- The most common honest score for solid work is 3 (medium ambition, adequate execution).
## Devil's Advocate (MANDATORY)
Before writing your final score, you MUST write all three of these:
1. **Case for LOWER:** Why might this work deserve a lower score? What was easy, what was avoided, what was less ambitious than it appears? Would a skeptical reviewer agree with your axis ratings?
2. **Case for HIGHER:** Why might this work deserve a higher score? What was genuinely challenging, surprising, or exceeded the original plan?
3. **Resolution:** If either case reveals you mis-rated an axis, re-rate it and recompute the matrix result. Then state your final score with a 1-2 sentence justification that addresses at least one point from each case.
If your devil's advocate is less than 3 sentences total, you're not engaging with it — try harder.
## Anti-Inflation Check
Check for a score history file at `.self-eval-scores.jsonl` in the current working directory.
If the file exists, read it and check the last 5 scores. If 4+ of the last 5 are the same number, flag it:
> **Warning: Score clustering detected.** Last 5 scores: [list]. Consider whether you're anchoring to a default.
If the file doesn't exist, ask yourself: "Would an outside observer rate this the same way I am?"
## Score Persistence
After presenting your evaluation, append one line to `.self-eval-scores.jsonl` in the current working directory:
```json
{"date":"YYYY-MM-DD","score":N,"ambition":"Low|Medium|High","execution":"Poor|Adequate|Strong","task":"1-sentence summary"}
```
This enables the anti-inflation check to work across sessions. If the file doesn't exist, create it.
## Output Format
Present your evaluation as:
## Self-Evaluation
**Task:** [1-sentence summary of what was attempted]
**Ambition:** [Low/Medium/High] — [1-sentence justification]
**Execution:** [Poor/Adequate/Strong] — [1-sentence justification]
**Devil's Advocate:**
- Lower: [why it might deserve less]
- Higher: [why it might deserve more]
- Resolution: [final reasoning]
**Score: [1-5]** — [1-sentence final justification]