---
name: sensei
description: "**WORKFLOW SKILL** — Iteratively improve skill frontmatter compliance using the Ralph loop pattern. WHEN: \"run sensei\", \"sensei help\", \"improve skill\", \"fix frontmatter\", \"skill compliance\", \"frontmatter audit\", \"score skill\", \"check skill tokens\". INVOKES: token counting tools, test runners, git commands. FOR SINGLE OPERATIONS: use token CLI directly for counts/checks."
license: MIT
metadata:
author: Microsoft
version: "1.0.5"
---
# Sensei
> "A true master teaches not by telling, but by refining." - The Skill Sensei
Automates skill frontmatter improvement using the [Ralph loop pattern](https://github.com/soderlind/ralph) - iteratively improving skills until they reach Medium-High compliance with passing tests, then checking token usage and prompting for action.
## Help
When user says "sensei help" or asks how to use sensei, show this:
```
╔══════════════════════════════════════════════════════════════════╗
║ SENSEI - Skill Frontmatter Compliance Improver ║
╠══════════════════════════════════════════════════════════════════╣
║ ║
║ USAGE: ║
║ Run sensei on <skill-name> # Single skill ║
║ Run sensei on <skill-name> --skip-integration # Fast mode ║
║ Run sensei on <skill1>, <skill2>, ... # Multiple skills ║
║ Run sensei on all Low-adherence skills # Batch by score ║
║ Run sensei on all skills # All skills ║
║ ║
║ EXAMPLES: ║
║ Run sensei on appinsights-instrumentation ║
║ Run sensei on azure-security --skip-integration ║
║ Run sensei on azure-security, azure-observability ║
║ Run sensei on all Low-adherence skills ║
║ ║
║ WHAT IT DOES: ║
║ 1. READ - Load skill's SKILL.md, tests, and token count ║
║ 2. SCORE - Check compliance (Low/Medium/Medium-High/High) ║
║ 3. SCAFFOLD - Create tests from template if missing ║
║ 4. IMPROVE - Add WHEN: triggers (cross-model optimized) ║
║ 5. TEST - Run tests, fix if needed ║
║ 6. REFERENCES- Validate markdown links ║
║ 7. TOKENS - Check token budget, gather suggestions ║
║ 8. SUMMARY - Show before/after with suggestions ║
║ 9. PROMPT - Ask: Commit, Create Issue, or Skip? ║
║ 10. REPEAT - Until Medium-High score + tests pass ║
║ ║
║ TARGET SCORE: Medium-High ║
║ ✓ Description > 150 chars, ≤ 60 words ║
║ ✓ Has "WHEN:" trigger phrases (preferred) ║
║ ✓ No "DO NOT USE FOR:" (unless disambiguation-critical) ║
║ ✓ SKILL.md < 500 tokens (soft limit) ║
║ ║
║ MORE INFO: ║
║ See .github/skills/sensei/README.md for full documentation ║
║ ║
╚══════════════════════════════════════════════════════════════════╝
```
## When to Use
- Improving a skill's frontmatter compliance score
- Adding trigger phrases and anti-triggers to skill descriptions
- Batch-improving multiple skills at once
- Auditing and fixing Low-adherence skills
## Invocation Modes
### Single Skill
```
Run sensei on azure-deploy
```
### Multiple Skills
```
Run sensei on azure-security, azure-observability
```
### By Adherence Level
```
Run sensei on all Low-adherence skills
```
### All Skills
```
Run sensei on all skills
```
### GEPA Mode (Deep Optimization)
```
Run sensei on my-skill --gepa
Run sensei on my-skill --gepa --skip-integration
Run sensei on all skills --gepa
```
When `--gepa` is used, Step 5 (IMPROVE) is replaced with GEPA evolutionary optimization.
Instead of template-based improvements, GEPA parses trigger prompt arrays from the existing
test harness and combines them with content quality heuristics to build a fitness function.
An LLM proposes and evaluates many candidate improvements automatically. Note: GEPA does not
execute Jest tests directly — it uses the test data (prompts) as evaluation inputs.
**GEPA score-only mode** (no LLM calls, just evaluate current quality):
```
Run sensei score my-skill
Run sensei score all skills
```
## The Ralph Loop
For each skill, execute this loop until score >= Medium-High AND tests pass:
1. **READ** - Load `plugin/skills/{skill-name}/SKILL.md`, tests, and token count
2. **SCORE** - Run spec-based compliance check (see [SCORING.md](references/SCORING.md)):
- Validate `name` per [agentskills.io spec](https://agentskills.io/specification) (no `--`, no start/end `-`, lowercase alphanumeric)
- Check description length and word count (≤60 words)
- Check triggers (WHEN: preferred, USE FOR: accepted)
- Warn on "DO NOT USE FOR:" (risky in multi-skill environments — **exception**: REQUIRED for skills that share trigger overlap with broader skills like `azure-prepare`)
- Preserve optional spec fields (`license`, `metadata`, `allowed-tools`) if present
3. **CHECK** - If score >= Medium-High AND tests pass → go to TOKENS step
4. **SCAFFOLD** - If `tests/{skill-name}/` doesn't exist, create from `tests/_template/`
5. **IMPROVE FRONTMATTER** - Add WHEN: triggers (stay under 60 words and 1024 chars)
5b. **IMPROVE WITH GEPA** (when `--gepa` flag is set) — Replaces step 5 (IMPROVE FRONTMATTER) with automated optimization; step 6 (IMPROVE TESTS) still runs normally:
- Auto-discovers `tests/{skill-name}/triggers.test.ts` and extracts prompt arrays
- Builds a GEPA evaluator scoring content quality + trigger accuracy based on those trigger prompt arrays (not Jest test pass/fail results)
- Runs `python .github/skills/sensei/scripts/gepa/auto_evaluator.py optimize --skill {skill-name} --skills-dir plugin/skills --tests-dir tests`
- Shows diff of optimized SKILL.md for user approval
- GEPA uses existing test trigger definitions as configuration — it does not execute, replace, or modify Jest tests
6. **IMPROVE TESTS** - Update `shouldTriggerPrompts` and `shouldNotTriggerPrompts` to match the finalized frontmatter (including any GEPA changes)
7. **VERIFY** - Run `cd tests && npm test -- --testPathPatterns={skill-name}`
8. **VALIDATE REFERENCES** - Run `cd scripts && npm run references {skill-name}` to check markdown links
9. **TOKENS** - Check token budget and line count (< 500 lines per spec), gather optimization suggestions
10. **SUMMARY** - Display before/after comparison with unimplemented suggestions
11. **PROMPT** - Ask user: Commit, Create Issue, or Skip?
12. **REPEAT** - Go to step 2 (max 5 iterations per skill)
## Scoring Criteria (Quick Reference)
Sensei validates skills against the [agentskills.io specification](https://agentskills.io/specification). See [SCORING.md](references/SCORING.md) for full details.
| Score | Requirements |
|-------|--------------|
| **Invalid** | Name fails spec validation (consecutive hyphens, start/end hyphen, uppercase, etc.) |
| **Low** | Basic description, no explicit triggers |
| **Medium** | Has trigger keywords/phrases, description > 150 chars, >60 words |
| **Medium-High** | Has "WHEN:" (preferred) or "USE FOR:" triggers, ≤60 words |
| **High** | Medium-High + compatibility field |
**Target: Medium-High** (distinctive triggers, concise description)
> ⚠️ "DO NOT USE FOR:" is **risky in multi-skill environments** (15+ overlapping skills) — causes keyword contamination on fast-pattern-matching models. Safe for small, isolated skill sets. Use positive routing with `WHEN:` for cross-model safety.
>
> **Exception — disambiguation-critical skills:** When a skill's `USE FOR` triggers directly overlap with a broader skill (e.g., `azure-prepare` owns "deploy to Azure"), `DO NOT USE FOR:` is **REQUIRED** to prevent the broader skill from capturing prompts that belong to the specialized skill. Removing it causes routing regressions. Integration tests validate this routing -- run them before removing any `DO NOT USE FOR:` clause.
**Strongly recommended** (reported as suggestions if missing):
- `license` — identifies the license applied to the skill
- `metadata.version` — tracks the skill version for consumers
## Frontmatter Template
Per the [agentskills.io spec](https://agentskills.io/specification), required and optional fields:
```yaml
---
name: skill-name
description: "[ACTION VERB] [UNIQUE_DOMAIN]. [One clarifying sentence]. WHEN: \"trigger 1\", \"trigger 2\", \"trigger 3\"."
license: MIT
metadata:
version: "1.0"
# Other optional spec fields — preserve if already present:
# metadata.author: example-org
# allowed-tools: Bash(git:*) Read
---
```
> **IMPORTANT:** Use inline double-quoted strings for descriptions. Do NOT use `>-` folded scalars (incompatible with skills.sh). Do NOT use `|` literal blocks (preserves newlines). Keep total description under 1024 characters and ≤60 words.
> ⚠️ **"DO NOT USE FOR:" carries context-dependent risk.** In multi-skill environments (10+ skills with overlapping domains), anti-trigger clauses introduce the very keywords that cause wrong-skill activation on Claude Sonnet and fast-pattern-matching models ([evidence](https://gist.github.com/kvenkatrajan/52e6e77f5560ca30640490b4cc65d109)). For small, isolated skill sets (1-5 skills), the risk is low. When in doubt, use positive routing with `WHEN:` and distinctive quoted phrases.
>
> **Exception:** `DO NOT USE FOR:` is **REQUIRED** when a specialized skill's triggers overlap with a broader skill (e.g., `azure-hosted-copilot-sdk` vs. `azure-prepare` on "deploy to Azure"). Without the negative discriminator, the broader skill captures prompts that should route to the specialized one. Always run integration tests before removing a `DO NOT USE FOR:` clause.
## Test Scaffolding
When tests don't exist, scaffold from `tests/_template/`:
```bash
cp -r tests/_template tests/{skill-name}
```
Then update:
1. `SKILL_NAME` constant in all test files
2. `shouldTriggerPrompts` - 5+ prompts matching new frontmatter triggers
3. `shouldNotTriggerPrompts` - 5+ prompts matching anti-triggers
**Commit Messages:**
```
sensei: improve {skill-name} frontmatter
```
## Constraints
- Only modify `plugin/skills/` - these are the Azure skills used by Copilot
- `.github/skills/` contains meta-skills like sensei for developer tooling
- Max 5 iterations per skill before moving on
- Description must stay under 1024 characters
- SKILL.md should stay under 500 tokens (soft limit)
- Tests must pass before prompting for action
- User chooses: Commit, Create Issue, or Skip after each skill
## Flags
| Flag | Description |
|------|-------------|
| `--skip-integration` | Skip integration tests for faster iteration. Only runs unit and trigger tests. |
| `--gepa` | Use GEPA evolutionary optimization instead of template-based improvement. Auto-discovers tests and builds evaluator at runtime. |
> ⚠️ Skipping integration tests speeds up the loop but may miss runtime issues. Consider running full tests before final commit.
## Reference Documentation
- [SCORING.md](references/SCORING.md) - Detailed scoring criteria
- [LOOP.md](references/LOOP.md) - Ralph loop workflow details
- [EXAMPLES.md](references/EXAMPLES.md) - Before/after examples
- [TOKEN-INTEGRATION.md](references/TOKEN-INTEGRATION.md) - Token budget integration
## Related Skills
- [markdown-token-optimizer](/.github/skills/markdown-token-optimizer) - Token analysis and optimization
- [skill-authoring](/.github/skills/skill-authoring) - Skill writing guidelines