npx claudepluginhub austinogilvie/promptkitFilesystem-based project management for Claude Code with specs, issues, and automatic context injection.
A collection of Claude Code skills, agents, and commands for enhanced AI-assisted development workflows.
promptkit provides reusable AI tooling components that extend Claude Code's capabilities. These components encode domain expertise, enforce best practices, and automate repetitive tasks across projects.
# Clone the repository
git clone https://github.com/austinogilvie/promptkit.git
# Copy skills to your user-level Claude Code config
cp -r promptkit/.claude/skills/* ~/.claude/skills/
# Or symlink for easy updates
ln -s $(pwd)/promptkit/.claude/skills/* ~/.claude/skills/
| Skill | Description |
|---|---|
| docs-writer | Generate comprehensive technical documentation—API references, user guides, architecture docs, ADRs, and runbooks. Includes templates and validation scripts. |
| readme-updater | Keep README files synchronized with code changes. Detects dependency updates, new features, and configuration changes that require documentation updates. |
| file-categorization | Classify project files using an 8-category taxonomy (Config, Tests, Docs, Scripts, Source Code, Data, AI Tooling, Other). Includes automated categorization script. |
| python-dunder-enforcer | Ensure Python classes include appropriate dunder methods (__repr__, __str__, comparisons). Enforces best practices and provides field ranking heuristics. |
| duckdb-setup | Initialize and configure DuckDB databases. Handles extensions, connection settings, and project structure with security best practices for .gitignore. |
| Agent | Description |
|---|---|
| data-profiler | Perform comprehensive dataset profiling before modeling or schema design. Analyzes field structures, type distributions, null percentages, nested objects, and generates schema recommendations. |
| Command | Description |
|---|---|
/create-skill | Scaffold a new Claude Code skill with proper structure (SKILL.md, scripts/, references/, assets/). |
/build-research-doc | Convert a directory of interlinked Markdown research files into a single DOCX with preserved structure, links, and auto-generated TOC via Pandoc. |
.claude/
├── agents/
│ └── data-profiler.md # Dataset profiling agent
├── commands/
│ ├── create-skill.md # Skill scaffolding command
│ ├── build-research-doc.md # Markdown-to-DOCX converter
│ └── scripts/
│ └── build_research_doc.py # Python script for build-research-doc
└── skills/
├── docs-writer/
│ ├── SKILL.md # Main skill definition
│ ├── workflows/ # Task-specific workflows
│ ├── templates/ # Documentation templates
│ ├── examples/ # Output samples
│ └── scripts/ # Validation tools
├── readme-updater/
│ ├── SKILL.md
│ ├── references/ # Patterns and templates
│ └── scripts/ # README checking tools
├── file-categorization/
│ ├── SKILL.md
│ ├── references/ # Pattern definitions
│ └── scripts/ # categorize.py
├── python-dunder-enforcer/
│ ├── SKILL.md
│ └── references/ # Examples and cheatsheets
└── duckdb-setup/
├── SKILL.md
├── references/ # Extension docs
├── scripts/ # init_duckdb.py
└── assets/ # SQL templates
Skills activate automatically based on context when Claude Code recognizes a matching task:
User: "Create a README for this project"
→ Claude activates docs-writer skill
User: "Categorize the files in this repo"
→ Claude activates file-categorization skill
User: "Add __repr__ to my Python class"
→ Claude activates python-dunder-enforcer skill
Agents are invoked via the Task tool for complex, multi-step operations:
User: "Profile this JSONL dataset before I build models"
→ Claude spawns data-profiler agent for comprehensive analysis
Commands are invoked with the slash prefix:
/create-skill api-client "Generate typed API clients from OpenAPI specs"
/build-research-doc ~/research/my-project
/build-research-doc ./docs/analysis --output final_report.docx
Install skills globally for use across all projects:
# Create Claude config directory if needed
mkdir -p ~/.claude/skills ~/.claude/agents ~/.claude/commands