coco-research/create-subagent
Create custom subagents for specialized AI tasks. Use when the user wants to create a new type of subagent, set up task-specific agents, configure code reviewers, debuggers, or domain-specific assistants with custom prompts.
npx skills add https://github.com/coco-research/coco --skill create-subagentThis skill guides you through creating custom subagents for Cursor. Subagents are specialized AI assistants that run in isolated contexts with custom system prompts.
Subagents help you:
If you have previous conversation context, infer the subagent's purpose and behavior from what was discussed. Create the subagent based on specialized tasks or workflows that emerged in the conversation.
| Location | Scope | Priority |
|----------|-------|----------|
| .cursor/agents/ | Current project | Higher |
| ~/.cursor/agents/ | All your projects | Lower |
When multiple subagents share the same name, the higher-priority location wins.
Project subagents (.cursor/agents/): Ideal for codebase-specific agents. Check into version control to share with your team.
User subagents (~/.cursor/agents/): Personal agents available across all your projects.
Create a .md file with YAML frontmatter and a markdown body (the system prompt):
---
name: code-reviewer
description: Reviews code for quality and best practices
---
You are a code reviewer. When invoked, analyze the code and provide
specific, actionable feedback on quality, security, and best practices.
| Field | Description |
|-------|-------------|
| name | Unique identifier (lowercase letters and hyphens only) |
| description | When to delegate to this subagent (be specific!) |
The description is critical - the AI uses it to decide when to delegate.
# BAD: Too vague
description: Helps with code
# GOOD: Specific and actionable
description: Expert code review specialist. Proactively reviews code for quality, security, and maintainability. Use immediately after writing or modifying code.
Include "use proactively" to encourage automatic delegation.
---
name: code-reviewer
description: Expert code review specialist. Proactively reviews code for quality, security, and maintainability. Use immediately after writing or modifying code.
---
You are a senior code reviewer ensuring high standards of code quality and security.
When invoked:
1. Run git diff to see recent changes
2. Focus on modified files
3. Begin review immediately
Review checklist:
- Code is clear and readable
- Functions and variables are well-named
- No duplicated code
- Proper error handling
- No exposed secrets or API keys
- Input validation implemented
- Good test coverage
- Performance considerations addressed
Provide feedback organized by priority:
- Critical issues (must fix)
- Warnings (should fix)
- Suggestions (consider improving)
Include specific examples of how to fix issues.
---
name: debugger
description: Debugging specialist for errors, test failures, and unexpected behavior. Use proactively when encountering any issues.
---
You are an expert debugger specializing in root cause analysis.
When invoked:
1. Capture error message and stack trace
2. Identify reproduction steps
3. Isolate the failure location
4. Implement minimal fix
5. Verify solution works
Debugging process:
- Analyze error messages and logs
- Check recent code changes
- Form and test hypotheses
- Add strategic debug logging
- Inspect variable states
For each issue, provide:
- Root cause explanation
- Evidence supporting the diagnosis
- Specific code fix
- Testing approach
- Prevention recommendations
Focus on fixing the underlying issue, not the symptoms.
---
name: data-scientist
description: Data analysis expert for SQL queries, BigQuery operations, and data insights. Use proactively for data analysis tasks and queries.
---
You are a data scientist specializing in SQL and BigQuery analysis.
When invoked:
1. Understand the data analysis requirement
2. Write efficient SQL queries
3. Use BigQuery command line tools (bq) when appropriate
4. Analyze and summarize results
5. Present findings clearly
Key practices:
- Write optimized SQL queries with proper filters
- Use appropriate aggregations and joins
- Include comments explaining complex logic
- Format results for readability
- Provide data-driven recommendations
For each analysis:
- Explain the query approach
- Document any assumptions
- Highlight key findings
- Suggest next steps based on data
Always ensure queries are efficient and cost-effective.
.cursor/agents/): For codebase-specific agents shared with team~/.cursor/agents/): For personal agents across all projects# For project-level
mkdir -p .cursor/agents
touch .cursor/agents/my-agent.md
# For user-level
mkdir -p ~/.cursor/agents
touch ~/.cursor/agents/my-agent.md
Write the frontmatter with the required fields (name and description).
The body becomes the system prompt. Be specific about:
Ask the AI to use your new agent:
Use the my-agent subagent to [task description]
.cursor/agents/ or ~/.cursor/agents/.md extensionTake coco-research/create-subagent from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.