general-skill-refiner

📁 przemocny/generic-skills 📅 6 days ago
1
总安装量
1
周安装量
#43098
全站排名
安装命令
npx skills add https://github.com/przemocny/generic-skills --skill general-skill-refiner

Agent 安装分布

replit 1
codex 1
claude-code 1
gemini-cli 1

Skill 文档

General Skill Refiner

Overview

Purpose: Critical analysis and improvement of agent skills

Approach:

  • Ruthless critique – identify all issues without sugar-coating
  • Clear priorities – MUST/SHOULD/NICE to have classification
  • Concrete solutions – specific fixes, not just complaints
  • User feedback loop – user decides what to fix
  • Verify changes – ensure quality after refactoring

Output: Improved skill + change report in .tasks/skill-refactoring-[date]/


Guidelines

What Makes a Good Skill

Based on Agent Skills Complete Guide:

  • Description is king – Most important field for skill triggering
  • Progressive disclosure – SKILL.md <500 lines, detailed docs in references/
  • Structure > prose – Numbered steps, bullet points, clear conditionals
  • Only add what LLM doesn’t know – No basic programming tutorials
  • One skill = one domain – Focused scope, not “everything-tool”
  • Include examples – Show input → output patterns
  • No time estimates – Never mention how long things take

Common Anti-Patterns to Look For

  • ❌ The Encyclopedia – 5000+ line SKILL.md (should split to references/)
  • ❌ The Everything Bagel – Skill applies to every task (should be a rule)
  • ❌ The Secret Handshake – Agent never loads skill (bad description)
  • ❌ The Fragile Skill – Hardcoded absolute paths (use relative paths)
  • ❌ The Wall of Text – Unstructured prose (needs headers/lists/steps)
  • ❌ Time Estimates – Any mention of duration (strictly forbidden)

Priority Levels

🔴 PRIORITY 1: MUST FIX (breaking issues)

  • Core guideline violations (time estimates, etc.)
  • Structural problems (too long, disorganized)
  • Missing critical functionality
  • Contradictions or confusion

🟡 PRIORITY 2: SHOULD FIX (quality issues)

  • Suboptimal workflow
  • Redundant content
  • Missing helpful features
  • Can be simplified

🟢 PRIORITY 3: NICE TO HAVE (enhancements)

  • Small improvements
  • Additional examples
  • Minor clarifications

Examples

Example 1: Identifying Time Estimates Problem

Skill analyzed: code-review

Problem found:

Line 45: "This analysis should take about 5-10 minutes"
Line 89: "Quick scan (2-3 minutes)"

Priority: 🔴 MUST FIX – Core guideline violation

Fix: Remove all time references:

Line 45: "This analysis covers security, performance, and style"
Line 89: "Quick scan of critical issues"

Example 2: Analysis Report Format

For skill: pdf-processor (1200 lines in SKILL.md)

Analysis presented to user:

## 🔴 MUST FIX

### 1. SKILL.md Too Long (1200 lines)
**Problem:** Exceeds recommended 500 line limit
**Impact:** Loads unnecessary content into context
**Fix:** Move detailed API docs to references/api-reference.md

### 2. Time Estimates Found
**Problem:** Lines 234, 456, 789 contain time estimates
**Fix:** Remove phrases "takes 2 minutes", "quick 30 second scan"

## 🟡 SHOULD FIX

### 3. Missing Examples Section
**Problem:** No concrete input → output examples
**Fix:** Add examples showing PDF processing workflow

## 🟢 What's Good
- Clear step-by-step workflow
- Good error handling coverage
- Scripts are well-documented

Example 3: Before/After Refactoring

Before:

## How to Use

So basically when you want to process a PDF you should first
check if the file exists and then you know, read it and extract
the text content which might take a few minutes depending on the
size, and then process it according to what the user needs...
  • Line count: 15 lines of prose
  • Structure: Wall of text
  • Time estimates: Yes (forbidden)

After:

## How to Use

**Process PDF files:**

1. Validate PDF exists
2. Extract text using `scripts/extract.py`
3. Parse output for required format
4. Return processed content

**For detailed extraction options, see [references/extraction-guide.md](references/extraction-guide.md)**
  • Line count: 11 lines
  • Structure: Clear numbered steps
  • Time estimates: None ✅

Workflow

Phase 1: Read & Understand

Cel: Dogłębnie zrozumieć skill i jego strukturę.

Kroki:

  1. Read main SKILL.md:

    • Zrozum cel i workflow
    • Zmierz długość (wc -l)
    • Zidentyfikuj główne phases
  2. Read wszystkie references:

    • Sprawdź co jest w references/
    • Zmierz długość każdego pliku
    • Zrozum jak references wspierają main skill
  3. Compare z innymi skillami:

    • Porównaj długość SKILL.md z innymi skillami
    • Sprawdź total długość references/
    • Zidentyfikuj pattern differences

Output: Pełne zrozumienie skilla i jego kontekstu.

Phase 2: Critical Analysis

Goal: Ruthlessly identify all problems and group by priority

Analysis Checklist:

Use references/quality-criteria.md for complete criteria. Key checks:

Structure & Length:

  • SKILL.md line count (target: <500 lines)
  • Total references/ size
  • Clear sections with headers
  • Numbered steps for procedures
  • Bullet points for criteria

Content Quality:

  • No time estimates anywhere (NEVER allowed)
  • No “wall of text” sections (needs structure)
  • No redundant content between SKILL.md and references/
  • Examples included (input → output)
  • Only adds what LLM doesn’t know

Description & Triggering:

  • Description contains specific keywords
  • Description explains WHEN to use
  • Triggers match how users talk about task
  • Not too broad (“everything-tool”)

Workflow & Features:

  • Clear step-by-step workflow
  • No missing critical features
  • No contradictions or confusion
  • Proper references to supporting files

For Each Issue Found:

  1. Identify: What is the specific problem? (with line numbers)
  2. Classify: 🔴 MUST / 🟡 SHOULD / 🟢 NICE priority
  3. Explain: Why is this a problem?
  4. Propose: Concrete solution (not just “fix this”)

Output: Complete prioritized list of issues with solutions

Phase 3: Present & Gather Feedback

Cel: Zaprezentować analizę użytkownikowi i zebrać feedback co poprawiać.

Presentation format:

## 🔴 Główne problemy (MUST FIX)

### 1. **[Problem name]**
**Problem:** [clear description]
**Konkretnie:** [specific examples with line numbers]
**Fix:** [concrete solution]

### 2. **[Problem name]**
...

## 🟡 Średnie problemy (SHOULD FIX)
[...]

## 🟢 Co jest dobre
[List positive aspects - important for balance]

## 💡 Sugestie poprawek

**Priority 1 (MUST fix):**
1. [Fix 1]
2. [Fix 2]

**Priority 2 (SHOULD fix):**
[...]

**Priority 3 (NICE to have):**
[...]

Zapytaj użytkownika:

  • “Zgadzasz się z tą analizą?”
  • “Czy są rzeczy z którymi się nie zgadzasz?”
  • “Powinienem wprowadzić te poprawki?”
  • “Czy jest coś specyficznego co chcesz zachować/zmienić?”

Listen for:

  • Co użytkownik zgadza się poprawić
  • Co użytkownik chce zachować (nawet jeśli jest suboptimal)
  • Dodatkowe insights od użytkownika

Output: Jasna lista co poprawiać z user approval.

Phase 4: Refactor

Cel: Systematycznie wprowadzić poprawki zgodnie z priorytetami i feedbackiem.

Refactoring workflow:

1. Start with Priority 1 issues:

  • Fix one issue at a time
  • Verify każdą zmianę
  • Don’t break other things

2. Then Priority 2:

  • Continue systematically
  • Show progress

3. Priority 3 if time:

  • Only if user wants
  • Quick wins first

Refactoring patterns:

Use references/refactoring-patterns.md:

  • How to remove time estimates
  • How to shorten SKILL.md (move to references)
  • How to simplify question flows
  • How to add missing features
  • How to improve structure

Best practices:

  • Make atomic changes
  • Test that files are valid
  • Keep backups (don’t worry, git)
  • Verify line counts after changes

Track changes: Create log in .tasks/skill-refactoring-[skill-name]-[date]/changes.md:

  • What was changed
  • Why
  • Before/after metrics

Phase 5: Verify & Report

Cel: Sprawdzić że wszystko działa i podsumować zmiany.

Verification checklist:

✅ Files are valid:

  • SKILL.md syntax OK
  • All references exist
  • No broken links

✅ Metrics improved:

  • SKILL.md shorter (if that was goal)
  • No time estimates
  • Better structure

✅ Quality checklist passed:

  • Run through quality-criteria.md
  • Wszystkie MUST fixes done
  • SHOULD fixes addressed

Report to user:

“Gotowe! Poprawiłem skill [name].

Główne zmiany:

  • [Change 1] – [metric before → after]
  • [Change 2] – [metric before → after]
  • [Change 3]

Metryki:

  • SKILL.md: [X] → [Y] linii
  • References: [X] → [Y] linii total
  • Issues fixed: [Priority 1: X, Priority 2: Y]

Co zostało poprawione: ✅ [Issue 1] ✅ [Issue 2] ✅ [Issue 3]

Co jest lepsze:

  • [Improvement 1]
  • [Improvement 2]

Szczegółowy raport w .tasks/skill-refactoring-[name]-[date]/

Zapytaj:

  • “Czy chcesz żebym przejrzał jeszcze raz?”
  • “Czy są dodatkowe poprawki?”

Special Cases

User disagrees z analizą

  • To OK – user ma final say
  • Explain reasoning ale respect decision
  • Document why recommendation was made
  • Proceed with user’s preferences

Skill jest fundamentalnie broken

  • Be honest: “Ten skill wymaga przepisania od zera”
  • Explain dlaczego
  • Zaproponuj: refactor vs rewrite from scratch
  • Let user decide

Multiple skille do poprawy

  • Jeden na raz
  • Priorytetyzuj który najpierw (ask user)
  • Apply learnings z jednego do innych

Refactoring reveals deeper issues

  • Stop and inform user
  • “Zauważyłem [deeper issue] – powinienem to też naprawić?”
  • Get approval before expanding scope

Quality Checklist

Przed zakończeniem, upewnij się że:

✅ Analysis was thorough: Checked all aspects z quality-criteria.md ✅ Problems prioritized: Clear MUST/SHOULD/NICE to have ✅ User feedback gathered: User approved changes ✅ Changes implemented: All agreed fixes done ✅ No time estimates: Removed all time references ✅ Structure improved: SKILL.md is clear and not too long ✅ References optimized: Supporting files helpful, not overwhelming ✅ Changes documented: Log created with before/after ✅ Verification done: Quality checklist passed ✅ User satisfied: Final approval received


Key Reminders

DO:

  • Be ruthlessly critical in Phase 2
  • Prioritize problems clearly (MUST/SHOULD/NICE)
  • Give concrete solutions, not just complaints
  • Get user feedback before big changes
  • Make atomic, verifiable changes
  • Document what you changed and why
  • Verify quality after refactoring

DON’T:

  • Don’t sugarcoat problems
  • Don’t fix without understanding
  • Don’t change everything at once
  • Don’t skip user feedback
  • Don’t ignore user preferences
  • Don’t forget to verify afterwards
  • Don’t leave broken files

Twoje podejście: Jesteś bezwzględnym code reviewer który chce żeby skill był najlepszy jaki może być. Identifikujesz problemy, proponujesz rozwiązania, ale ostatecznie user decyduje co poprawiać.

Pamiętaj:

  • Skill quality matters – bad skills = bad results
  • Be specific – “line 45 has time estimate” not “too many time estimates”
  • Priorities are key – fix breaking issues first
  • User knows their use case – respect their input
  • Document changes – future you will thank you
  • Verify everything – broken skill is worse than unchanged skill