github-to-skills

| Skill | Description |

|-------|-------------|

| [github-to-skills](./github-to-skills/) | Convert GitHub repos into AI skills automatically |

| [skill-manager](./skill-manager/) | Manage skill lifecycle - check updates, list, delete |

| [skill-evolution-manager](./skill-evolution-manager/) | Evolve skills based on user feedback and experience |

---

Automated factory for converting GitHub repositories into specialized AI skills.

Features

• Fetches repository metadata (README, latest commit hash)
• Creates standardized skill directory structure
• Generates SKILL.md with extended frontmatter for lifecycle management
• Creates wrapper scripts for tool invocation

Usage

```

/github-to-skills

```

Or: "Package this repo into a skill: "

Example

```

/github-to-skills https://github.com/yt-dlp/yt-dlp

```

---

Lifecycle manager for GitHub-based skills.

Features

• Audit: Scan local skills folder for GitHub-based skills
• Check: Compare local commit hashes against remote HEAD
• Report: Generate status report (Stale/Current)
• Update: Guided workflow for upgrading skills
• Inventory: List all skills, delete unwanted ones

Usage

```

/skill-manager check # Scan for updates

/skill-manager list # List all skills

/skill-manager delete # Remove a skill

```

Scripts

| Script | Purpose |

|--------|---------|

| scan_and_check.py | Scan directories, parse frontmatter, check remote versions |

| update_helper.py | Backup files before update |

| list_skills.py | List installed skills with metadata |

| delete_skill.py | Permanently remove a skill |

---

Continuously improve skills based on user feedback and conversation insights.

Core Concepts

1. Session Review: Analyze skill performance after conversations
2. Experience Extraction: Convert feedback into structured evolution.json
3. Smart Stitching: Persist learned best practices into SKILL.md

Usage

```

/evolve

```

Or: "Save this experience to the skill"

Workflow

1. Review: Agent analyzes what worked/didn't work
2. Extract: Creates structured JSON with preferences, fixes, custom prompts
3. Persist: Merges into evolution.json
4. Stitch: Updates SKILL.md with learned best practices

Scripts

| Script | Purpose |

|--------|---------|

| merge_evolution.py | Incrementally merge new experience data |

| smart_stitch.py | Generate/update best practices section in SKILL.md |

| align_all.py | Batch re-stitch all skills after updates |

---

1. Clone this repository:

```bash

git clone https://github.com/KKKKhazix/Khazix-Skills.git

```

1. Copy desired skills to your Claude skills directory:

```bash

# Windows

copy /E Khazix-Skills\github-to-skills %USERPROFILE%\.claude\skills\

# macOS/Linux

cp -r Khazix-Skills/github-to-skills ~/.claude/skills/

```

1. Restart Claude to load the new skills.

---

• Python 3.8+
• Git (for checking remote repositories)
• PyYAML (pip install pyyaml)

---

```

+------------------+ +----------------+ +------------------------+

| github-to-skills | --> | skill-manager | --> | skill-evolution-manager|

+------------------+ +----------------+ +------------------------+

| | |

Create new Maintain & Evolve &

skills from update skills improve based

GitHub repos on feedback

```

The Complete Skill Lifecycle:

1. Create: Use github-to-skills to wrap a GitHub repo as a skill
2. Maintain: Use skill-manager to check for updat