Turn Cursor into a multi-agent powerhouse. Autonomous workflows, parallel research, specialized subagents — all running natively inside your IDE. No external process. No API key.
For developers who can't access Claude Code (or prefer Cursor), this project bridges the gap by bringing Claude-style autonomous agent capabilities directly into your existing IDE.
The agent decomposes complex tasks, spawns specialized subagents in parallel, synthesizes results, and delivers polished output — just like Claude Code's autonomous mode.
Domain-specific capabilities installed as plug-and-play modules. Install what you need, ignore what you don't.
One bash install.sh and everything works in every project. No docker, no daemon, no API keys.
git clone https://github.com/cocolwy/cursor-agents.git
cd cursor-agents
bash deploy/install.shOpen any project in Cursor and start using commands.
After install, open any project in Cursor and type these prompts directly in the chat:
Build a feature end-to-end:
/code Add user authentication with JWT — register, login, and refresh token endpoints
→ Planner designs the approach → Coder implements → Tester writes & runs tests → Reviewer checks quality → auto-fix if needed.
Refactor existing code:
/refactor Extract the database logic from controllers into a repository layer
Research then execute:
/goal Evaluate whether we should migrate from Express to Fastify, then do it if it makes sense
→ Defines success criteria → parallel research → plans → executes → verifies the goal is actually achieved → if not, iterates with a different approach (up to 5 rounds). Doesn't stop until the goal is met or proven infeasible.
Financial modeling:
/comps Tesla NIO BYD — comparable company analysis
/dcf Apple — DCF valuation, assume 12% revenue growth over 5 years
Bootstrap a new project:
/init
→ Scans your codebase and generates .cursor/rules/project-context.mdc so Cursor understands your project in every future conversation.
Create a structured PR:
/pr
→ Analyzes your diff, drafts title + summary + test plan, shows you the draft, then creates the PR.
Daily workflow (review → commit):
/review
/commit
→ /review checks your changes for bugs and security issues. /commit generates a quality commit message and commits.
Generate tests:
/test src/utils/parser.ts
→ Analyzes the file, writes comprehensive tests (happy path + edge cases + errors), runs them.
That's it. No config files, no setup, no API keys — just prompt and go.
These work in any project, for any task:
| Command | What it does |
|---|---|
/code <task> |
Plan → Implement → Test → Review → Fix |
/refactor <task> |
Analyze → Refactor → Verify → Review |
/goal <task> |
Research → Plan → Execute → Verify until done |
/init |
Scan project → Generate context rules for Cursor |
/doctor |
Check installation health → Report issues |
/pr |
Analyze diff → Draft PR → Create via gh CLI |
/review |
Review uncommitted changes → Structured feedback |
/commit |
Analyze diff → Generate message → Commit |
/test <file> |
Analyze code → Write tests → Run them |
/code Add WebSocket support to my Express server with reconnection logic
Spawns a planner agent to design the approach, a coder agent to implement, runs tests, then a reviewer agent checks for bugs and security issues.
/refactor Extract the authentication logic into a reusable middleware
Analyzes dependencies, refactors safely, verifies tests pass, reviews for regressions.
/goal Research the best approach for migrating from REST to GraphQL in our codebase
Launches 3 parallel research agents (schema design, migration strategy, performance implications), synthesizes findings into an actionable plan.
Institutional-grade financial modeling with Excel output. Adapted from Anthropic's financial-services.
| Command | What it does |
|---|---|
/comps <companies> |
Comparable company analysis → .xlsx |
/dcf <company> |
DCF valuation model → .xlsx |
/lbo <company> |
Leveraged buyout model → .xlsx |
/competitive <company> |
Competitive landscape analysis |
/comps NVIDIA vs AMD vs Intel
Parallel research agents gather financials from SEC filings, then a financial analyst agent builds a formatted Excel comps table with operating metrics, valuation multiples, and statistical summary.
/dcf AAPL
Builds a 5-year DCF model with WACC, terminal value, and sensitivity tables — all as live Excel formulas.
- DevOps —
/deploy,/monitor,/incident(planned) - Data Science —
/eda,/pipeline,/visualize(planned) - Content —
/blog,/docs,/translate(planned)
Want to build a skill pack? See Contributing.
~/.cursor/
├── skills/ # Workflow definitions (SKILL.md files)
│ ├── agent-system/ # Master orchestrator (core)
│ ├── comps-analysis/ # ── Financial Pack ──
│ ├── dcf-model/ #
│ ├── lbo-model/ #
│ ├── competitive-analysis/ #
│ └── xlsx-author/ # Excel generation utility
└── agents/ # Subagent role definitions
├── planner.md # Architecture & decomposition
├── coder.md # Implementation specialist
├── reviewer.md # Code review & quality
├── researcher.md # Research & data gathering
└── financial-analyst.md # Financial modeling (Finance Pack)
How it works:
- You type a command (e.g.,
/code add caching) - Cursor's agent reads the
agent-systemskill → becomes the supervisor - Supervisor spawns specialized subagents via Cursor's built-in Task tool
- Subagents work in parallel where possible
- Supervisor synthesizes results and presents final output
No external runtime. No daemon. The intelligence lives in the skill definitions.
- Cursor IDE installed
- Any Cursor subscription (skills use your existing model access)
bash deploy/install.shrm -rf ~/.cursor/skills ~/.cursor/agentsFor CI/CD pipelines or external scripts, the project also includes a TypeScript orchestrator using @cursor/sdk:
npm install
export CURSOR_API_KEY=your_key
npx tsx src/main.ts code "Add rate limiting to the API"This is optional — the primary use case is the native in-IDE experience.
Contributions welcome! Here's how to add a new Skill Pack:
- Create a directory under
deploy/skills/your-skill-name/ - Write a
SKILL.mdwith YAML frontmatter (name,description) and workflow instructions - If your pack needs a specialist agent, add it to
deploy/agents/ - Register your commands in
deploy/skills/agent-system/SKILL.md - Run
bash deploy/install.shto test - Submit a PR
Areas where help is needed:
- New skill packs (DevOps, data science, content creation)
- Better data sourcing for financial skills
- Localization (Chinese docs, A-share market support)
- Real-world workflow testing
MIT