# Pal Analyze

> Run learning analysis — surface rating trends, recurring failure patterns, and graduation candidates. Use when learning analysis is due, or when the user asks about performance patterns, low ratings, or what to improve.

- Skill: `kovrichard/pal-analyze` (Agent Skill)
- Install (CLI): `npx skillmds@latest add kovrichard/pal-analyze`
- Raw SKILL.md: https://api.skillmd.com/api/skills/kovrichard/pal-analyze/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- License: MIT
- Author: kovrichard (https://skillmd.com/u/kovrichard)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/kovrichard/pal-analyze

---


When `/pal-analyze` is invoked (by you in response to a nudge, or by the user directly):

## 1. Run the analyze tool

```bash
pal cli analyze
```

If the user passed `--actionable` or wants recommendations, append it: `pal cli analyze --actionable`

## 2. Parse and present the output

Read the console output and summarize the key signals. Focus on what's actionable, not exhaustive lists:

**Ratings section:**
- Lead with the average and trend direction
- Call out any striking low-rating clusters (e.g. "47 low ratings, mostly around scope drift corrections")

**Graduation candidates:**
- Name the top 1-3 patterns ready to crystallize
- Suggest the wisdom domain they'd live in

**Emerging patterns:**
- Name any 2-occurrence patterns worth watching

Format example:
```
Analysis complete:

Ratings: X.X/10 avg | N low (≤4) | N high (≥7)
Top low-rating context: "[cluster description]"

Ready to graduate (3+ occurrences):
- "[pattern]" → suggest adding to wisdom/[domain].md

Emerging (2 occurrences — one more to graduate):
- "[pattern]"
```

## 3. Offer to act

After showing results, ask:
> "Want to crystallize any of these into a wisdom frame, or dig into the low-rating clusters?"

If yes to crystallizing:
```bash
pal cli wisdom-frame --domain <domain> --observation "<principle>"
```