Claudekit is an open-source AI development toolkit designed for Claude Code, featuring over 27 commands and 34 skills to enhance coding productivity. Ideal for developers looking to streamline their workflow and automate tasks, it offers a free solution for efficient code generation.
claude install duthaho/claudekitClaudekit is an open-source AI development toolkit designed for Claude Code, featuring over 27 commands and 34 skills to enhance coding productivity. Ideal for developers looking to streamline their workflow and automate tasks, it offers a free solution for efficient code generation.
[{"step":"Identify your development task and target language/framework","action":"Use `claude list-commands` to see available tools in Claudekit. For example, if building a React app, note commands like `generate-component` or `optimize-bundle`.","tip":"Combine multiple commands for end-to-end workflows. For instance, generate a component, then optimize its bundle size, and finally generate tests for it."},{"step":"Generate initial code structure","action":"Use `claude generate-[type]` commands with your project specifications. For backend work, use `claude generate-api --framework [FRAMEWORK] --db [DATABASE]`.","tip":"Include `--verbose` flag to get detailed explanations of generated code. This helps you learn best practices for future implementations."},{"step":"Optimize and refactor the generated code","action":"Run `claude optimize-code` with specific targets like `--target performance` or `--target security`. For frontend projects, use `claude bundle-analyze`.","tip":"Use `--diff` flag to preview changes before applying them. This prevents breaking changes in production code."},{"step":"Add testing and documentation","action":"Generate tests with `claude generate-tests` and documentation with `claude generate-docs`. Set coverage targets with `--coverage [PERCENTAGE]`.","tip":"For CI/CD pipelines, use `--output-format json` to easily parse results for automated workflows."},{"step":"Iterate and refine","action":"Use `claude review-code` to get suggestions for improvements based on your project's style guide or specific requirements.","tip":"Save your workflows as shell scripts for repeated use. For example, create `setup-dev.sh` that runs all generation commands in sequence."}]
Automating repetitive coding tasks
Generating code snippets quickly
Enhancing developer productivity with AI commands
Streamlining workflow for software projects
claude install duthaho/claudekitgit clone https://github.com/duthaho/claudekitCopy the install command above and run it in your terminal.
Launch Claude Code, Cursor, or your preferred AI coding agent.
Use the prompt template or examples below to test the skill.
Adapt the skill to your specific use case and workflow.
Use Claudekit to [TASK] in a [PROGRAMMING_LANGUAGE] project. Follow these steps: 1) Generate the necessary code snippets using [CLAUDE_COMMAND], 2) Optimize the code for performance with [CLAUDE_SKILL], 3) Add unit tests using [CLAUDE_COMMAND], and 4) Generate documentation with [CLAUDE_SKILL]. Ensure the output is production-ready and follows best practices for [PROGRAMMING_LANGUAGE].
### Claudekit Code Generation & Optimization for a Python REST API
**Task:** Build a scalable FastAPI backend for a task management app with PostgreSQL integration.
**Step 1: Generate Initial Code Structure**
```bash
claude generate-api --framework fastapi --db postgresql --name task-manager
```
Output:
```python
# task_manager/main.py
from fastapi import FastAPI
from task_manager.routers import tasks
app = FastAPI()
app.include_router(tasks.router)
```
**Step 2: Optimize Performance**
```bash
claude optimize-code --language python --target performance --file task_manager/main.py
```
Optimized output:
```python
# Added async support and connection pooling
from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware
from task_manager.routers import tasks
from task_manager.db import get_db
app = FastAPI()
app.add_middleware(
CORSMiddleware,
allow_origins=["*"],
allow_methods=["*"],
)
```
**Step 3: Generate Unit Tests**
```bash
claude generate-tests --language python --coverage 90 --file task_manager/routers/tasks.py
```
Test output:
```python
# tests/test_tasks.py
from fastapi.testclient import TestClient
from task_manager.main import app
client = TestClient(app)
def test_create_task():
response = client.post("/tasks", json={"title": "Test Task"})
assert response.status_code == 201
assert response.json()["title"] == "Test Task"
```
**Step 4: Generate Documentation**
```bash
claude generate-docs --format openapi --file task_manager/main.py --output docs/api.yaml
```
Documentation snippet:
```yaml
# docs/api.yaml
paths:
/tasks:
post:
summary: Create a new task
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/Task'
responses:
'201':
description: Task created successfully
```
**Final Output:**
- Generated 8 API endpoints
- Optimized database queries with async/await
- Achieved 92% test coverage
- Auto-generated OpenAPI 3.1 docsAI assistant built for thoughtful, nuanced conversation
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