subagent-creator

tech-leads-club/agent-skills · updated Apr 8, 2026

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$npx skills add https://github.com/tech-leads-club/agent-skills --skill subagent-creator
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summary

This skill provides guidance for creating effective, agent-agnostic subagents.

skill.md

Subagent Creator

This skill provides guidance for creating effective, agent-agnostic subagents.

What are Subagents?

Subagents are specialized assistants that an AI agent can delegate tasks to. Characteristics:

  • Isolated context: Each subagent has its own context window
  • Parallel execution: Multiple subagents can run simultaneously
  • Specialization: Configured with specific prompts and expertise
  • Reusable: Defined once, used in multiple contexts

When to Use Subagents vs Skills

Is the task complex with multiple steps?
├─ YES → Does it require isolated context?
│         ├─ YES → Use SUBAGENT
│         └─ NO → Use SKILL
└─ NO → Use SKILL

Use Subagents for:

  • Complex workflows requiring isolated context
  • Long-running tasks that benefit from specialization
  • Verification and auditing (independent perspective)
  • Parallel workstreams

Use Skills for:

  • Quick, one-off actions
  • Domain knowledge without context isolation
  • Reusable procedures that don't need isolation

Subagent Structure

A subagent is typically a markdown file with frontmatter metadata:

---
name: agent-name
description: Description of when to use this subagent.
model: inherit # or fast, or specific model ID
readonly: false # true to restrict write permissions
---

You are an [expert in X].

When invoked:

1. [Step 1]
2. [Step 2]
3. [Step 3]

[Detailed instructions about expected behavior]

Report [type of expected result]:

- [Output format]
- [Metrics or specific information]

Subagent Creation Process

1. Define the Purpose

  • What specific responsibility does the subagent have?
  • Why does it need isolated context?
  • Does it involve multiple complex steps?
  • Does it require deep specialization?

2. Configure the Metadata

name (required)

Unique identifier. Use kebab-case.

name: security-auditor

description (critical)

CRITICAL for automatic delegation. Explains when to use this subagent.

Good descriptions:

  • "Security specialist. Use when implementing auth, payments, or handling sensitive data."
  • "Debugging specialist for errors and test failures. Use when encountering issues."
  • "Validates completed work. Use after tasks are marked done."

Phrases that encourage automatic delegation:

  • "Use proactively when..."
  • "Always use for..."
  • "Automatically delegate when..."

model (optional)

model: inherit  # Uses same model as parent (default)
model: fast     # Uses fast model for quick tasks

readonly (optional)

readonly: true # Restricts write permissions

3. Write the Subagent Prompt

Define:

  1. Identity: "You are an [expert]..."
  2. When invoked: Context of use
  3. Process: Specific steps to follow
  4. Expected output: Format and content

Template:

You are an [expert in X] specialized in [Y].

When invoked:

1. [First action]
2. [Second action]
3. [Third action]

[Detailed instructions about approach]

Report [type of result]:

- [Specific format]
- [Information to include]
- [Metrics or criteria]

[Philosophy or principles to follow]

Common Subagent Patterns

1. Verification Agent

Purpose: Independently validates that completed work actually works.

---
name: verifier
description: Validates completed work. Use after tasks are marked done.
model: fast
---

You are a skeptical validator.

When invoked:

1. Identify what was declared as complete
2. Verify the implementation exists and is functional
3. Execute tests or relevant verification steps
4. Look for edge cases that may have been missed

Be thorough. Report:

- What was verified and passed
- What is incomplete or broken
- Specific issues to address

2. Debugger

Purpose: Expert in root cause analysis.

---
name: debugger
description: Debugging specialist. Use when encountering errors or test failures.
---

You are a debugging expert.

When invoked:

1. Capture the error message and stack trace
2. Identify reproduction steps
3. Isolate the failure location
4. Implement minimal fix
5. Verify the solution works

For each issue, provide:

- Root cause explanation
- Evidence supporting the diagnosis
- Specific code fix
- Testing approach

3. Security Auditor

Purpose: Security expert auditing code.

---
name: security-auditor
description: Security specialist. Use for auth, payments, or sensitive data.
---

You are a security expert.

When invoked:

1. Identify security-sensitive code paths
2. Check for common vulnerabilities
3. Confirm secrets are not hardcoded
4. Review input validation

Report findings by severity:

- **Critical** (must fix before deploy)
- **High** (fix soon)
- **Medium** (address when possible)
- **Low** (suggestions)

4. Code Reviewer

Purpose: Code review with focus on quality.

---
name: code-reviewer
description: Code review specialist. Use when changes are ready for review.
---

You are a code review expert.

When invoked:

1. Analyze the code changes
2. Check readability, performance, patterns, error handling
3. Identify code smells and potential bugs
4. Suggest specific improvements

Report:
**✅ Approved / ⚠️ Approved with caveats / ❌ Changes needed**

**Issues Found:**

- **[Severity]** [Location]: [Issue]
  - Suggestion: [How to fix]

Best Practices

✅ DO

  • Write focused subagents: One clear responsibility
  • Invest in the description: Determines when to delegate
  • Keep prompts concise: Direct and specific
  • Share with team: Version control subagent definitions
  • Test the description: Check correct subagent is triggered

❌ AVOID

  • Vague descriptions: "Use for general tasks" gives no signal
  • Prompts too long: 2000 words don't make it smarter
  • Too many subagents: Start with 2-3 focused ones

Quality Checklist

Before finalizing:

  • Description is specific about when to delegate
  • Name uses kebab-case
  • One clear responsibility (not generic)
  • Prompt is concise but complete
  • Instructions are actionable
  • Output format is well defined
  • Model configuration appropriate

Output Messages

When creating a subagent:

✅ Subagent created successfully!

📁 Location: .agent/subagents/[name].md
🎯 Purpose: [brief description]
🔧 How to invoke:
   - Automatic: Agent delegates when it detects [context]
   - Explicit: /[name] [instruction]

💡 Tip: Include keywords like "use proactively" to encourage delegation.
how to use subagent-creator

How to use subagent-creator on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add subagent-creator
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/tech-leads-club/agent-skills --skill subagent-creator

The skills CLI fetches subagent-creator from GitHub repository tech-leads-club/agent-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/subagent-creator

Reload or restart Cursor to activate subagent-creator. Access the skill through slash commands (e.g., /subagent-creator) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.735 reviews
  • Noah Torres· Dec 24, 2024

    subagent-creator reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Kabir Taylor· Dec 8, 2024

    subagent-creator is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Rahul Santra· Nov 27, 2024

    Useful defaults in subagent-creator — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Camila Kapoor· Nov 27, 2024

    Keeps context tight: subagent-creator is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Valentina Liu· Nov 15, 2024

    subagent-creator has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Anaya Kapoor· Oct 26, 2024

    Solid pick for teams standardizing on skills: subagent-creator is focused, and the summary matches what you get after install.

  • Pratham Ware· Oct 18, 2024

    Registry listing for subagent-creator matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Diego Ramirez· Oct 18, 2024

    I recommend subagent-creator for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Sofia Verma· Oct 6, 2024

    subagent-creator fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Diego Perez· Sep 25, 2024

    Useful defaults in subagent-creator — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

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