skill-jit

Skill-JIT

Let Agents Learn and Persist Skills on the Fly

🐙 GitHub  |  📄 Blog

Installation

# Claude Code
claude plugin marketplace add china-qijizhifeng/skill-jit
claude plugin install skill-jit@skill-jit-marketplace

# OpenClaw
openclaw plugins install skill-jit --marketplace china-qijizhifeng/skill-jit

How It Works

Skill-JIT uses a two-agent architecture:

1. Researcher — Deep-dives into documentation, tests commands, verifies behaviors, and returns structured knowledge with evidence.
2. Writer — Decomposes tasks, orchestrates researchers, selects the right skill pattern, and generates production-ready skill files.

Workflow

User Request → Parse Input → Detect Mode (Create / Fix)
  → Capture Intent (what, when, output, edge cases)
  → Spawn Writer Agent → Writer spawns Researcher(s)
  → Combine Research → Select Pattern → Write Skill Files

Skill Patterns

Skills are generated following one of five proven patterns:

Pattern	Use When	Example
Tool Wrapper	Teaching how to use a tool/API/CLI	ffmpeg, Stripe SDK
Generator	Producing artifacts with fixed structure	Changelogs, API docs
Reviewer	Checking/auditing against criteria	Code review, security audit
Inversion	Agent needs user decisions before acting	Project scaffolding, config wizards
Pipeline	Strict sequential workflow with gates	Build → test → deploy

Patterns can be composed (e.g., Generator + Inversion, Pipeline + Reviewer).

Output Structure

Generated skills follow progressive disclosure:

.claude/skills/<skill-name>/
├── SKILL.md              # Main skill (frontmatter + body, <500 lines)
├── references/           # Deep-dive docs, parameters, troubleshooting
├── templates/            # Output templates (Generator pattern)
├── rubrics/              # Checklists (Reviewer pattern)
└── scripts/              # Helper scripts

Usage

Create a new skill

/skill-jit Create a skill for ffmpeg video-to-GIF conversion

Fix an existing skill

/skill-jit Fix the ffmpeg-gif skill — palette generation fails on macOS

Dry run (preview without writing)

/skill-jit --dry-run Create a skill for Docker multi-stage builds

External Services

Skill-JIT integrates with MCP servers for enhanced research:

• Context7 — API documentation aggregator
• DeepWiki — Wiki knowledge system
• GitMCP — Git-based documentation

Design Principles

• Explicit by Default — Every step has one clear action; no "use your judgment"
• Research-Grounded — Trust test results over documentation
• Generalize, Don't Overfit — Skills are reusable, not task-specific
• Progressive Disclosure — Frontmatter → body → bundled resources

License

MIT

Author

KYLN24