agent-writer

name	agent-writer
description	Create and update agent definition files following Anthropic best practices. Use when writing agent files, creating subagents, designing agent systems, or troubleshooting agent discovery and delegation issues.

Agent Writer

Create well-structured agent definition files for Claude Code following Anthropic's best practices for subagents and multi-agent systems.

Quick Start

Creating a new agent:

1. Determine the agent's single, focused purpose
2. Choose appropriate scope (project, user, or plugin)
3. Define tool allowlist (principle of least privilege)
4. Write clear identity and workflow instructions
5. Validate frontmatter and test delegation

When to Use This Skill

• Creating a new agent definition file
• Updating existing agent files to follow best practices
• Designing multi-agent systems with coordinators and specialists
• Troubleshooting agent discovery or delegation issues
• Converting workflows or prompts into specialized agents
• Implementing handoff protocols between agents

Agent File Structure

Agent definitions use Markdown files with YAML frontmatter:

---
name: agent-name
description: When to use this agent
tools:
  allowed:
    - Read
    - Grep
    - Glob
model: sonnet
---

# Agent Identity

You are a [role] specializing in [domain].

## Workflow

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

## Deliverables

Provide output in this format:
- [Structure]

## Guardrails

**NEVER:**
- [Anti-pattern 1]

**ALWAYS:**
- [Best practice 1]

File Locations

Scope	Location	Use When
Project	.claude/agents/	Agent is codebase-specific, version controlled
User	~/.claude/agents/	Personal agent used across all projects
Plugin	<plugin>/agents/	Distributing via plugin system

Priority: Managed > CLI > Project > User > Plugin

Essential Frontmatter Fields

Required Fields

name:

• Lowercase letters and hyphens only
• Max 64 characters
• Must be unique across scope

name: code-reviewer
name: ai-marketplace:compile-debug  # Plugin namespace

description:

• Critical for automatic delegation
• Include what it does AND when to use it
• Use specific trigger words

# Good - specific with triggers
description: "Expert code review specialist. Proactively reviews code for quality, security, and maintainability. Use immediately after writing or modifying code."

# Bad - too vague
description: "Helper agent"

Common Optional Fields

tools: - Principle of least privilege

tools:
  allowed:
    - Read
    - Grep
    - Glob

model: - Strategic assignment

model: opus      # High-stakes reviews
model: haiku     # Fast exploration

skills: - Preload context

skills:
  - compile-bisect
  - pytorch-inductor

For complete field reference, see reference.md

Writing Effective Descriptions

Formula: [What it does] + [When to use it] + [Key triggers]

✅ Good:

description: "Skill-driven debugger specialist for automatically isolating compilation failures. Use when debugging torch.compile errors, crashes, or incorrect output to identify which backend/subsystem fails."

❌ Too vague:

description: "Helper agent"

Tips:

• Include specific operations ("bisect", "review", "debug")
• Mention domains ("torch.compile", "code", "SQL")
• Add context clues ("Use when...", "Use immediately after...")
• Include "use proactively" for automatic invocation

System Prompt Structure

Recommended Pattern

# Agent Name

## Identity

You are a [role] specializing in [domain]. Your role is to:
- [Primary responsibility 1]
- [Primary responsibility 2]

**Scope**: [What's in scope]
**Not in scope**: [What to delegate]

## Deliverables

Return [format] in this structure:
[Expected output format]

## Workflow

1. **[Phase 1]**
   - [Steps]
   - [Expected outcome]

2. **[Phase 2]**
   - [Steps]
   - [Expected outcome]

## Guardrails

**NEVER:**
- [Anti-pattern with reason]

**ALWAYS:**
- [Best practice with reason]

Tool Access Patterns

Principle of Least Privilege

Grant only the tools necessary for the agent's purpose.

Read-Only Analysis:

tools:
  allowed:
    - Read
    - Grep
    - Glob

Code Modification:

tools:
  allowed:
    - Read
    - Edit
    - Write
    - Grep
    - Glob

Tools Never Available to Subagents

• Agent (no nesting)
• AskUserQuestion
• EnterPlanMode
• ExitPlanMode
• ScheduleWakeup

Multi-Agent Patterns

Coordinator Pattern

Routes tasks to specialists and synthesizes responses:

callable_agents:
  - specialist-1
  - specialist-2
parent_agent: null

Specialist Pattern

Deep expertise in specific domain:

callable_agents:
  - compile-debug
parent_agent: compile-debug

For detailed patterns, see reference.md

Context Isolation

Critical: Subagents start with fresh context.

Subagents receive:

• Their own system prompt
• The delegation prompt from parent
• Project CLAUDE.md files
• Preloaded skills

Subagents do NOT receive:

• Parent conversation history
• Parent tool call results

Best Practice: Include necessary context in delegation prompt.

# Bad - assumes prior knowledge
"Continue with the approach we discussed"

# Good - provides full context
"Implement OAuth 2.0 with JWT tokens. Files: src/auth/login.py, src/auth/tokens.py. Requirements: 1hr token expiry, refresh support."

Common Anti-Patterns

❌ Vague descriptions - "Helper agent" ✅ Specific descriptions - "Skill-driven debugger for torch.compile failures"

❌ Overly broad scope - One agent doing everything ✅ Focused purpose - Single, specific capability

❌ Excessive tool access - Read-only agent with Write/Edit ✅ Least privilege - Only necessary tools

❌ Missing context - "Debug the issue" ✅ Full context - "Debug auth failure in login.py. Error: 'Invalid token'. Stack trace: [...]"

Validation Checklist

Frontmatter

• name is lowercase, hyphens only, max 64 chars
• description is specific and < 1024 chars
• YAML is valid (no tabs, correct indentation)
• tools uses least privilege
• model matches task complexity

System Prompt

• Clear identity and scope
• Explicit deliverable format
• Step-by-step workflow
• NEVER/ALWAYS guardrails
• Concrete examples

Testing

• Description triggers automatic delegation
• Agent receives necessary context
• Agent produces expected format

Examples

See examples.md for complete agent definitions:

• Read-Only Specialist (code-reviewer)
• Skill-Driven Orchestrator (debug-coordinator)
• Skill-Driven Orchestrator (compile-debug)

Advanced Topics

See reference.md for:

• Complete frontmatter field reference
• Worktree isolation patterns
• Security best practices (permission modes, hooks)
• Handoff protocols and JSON schemas
• Multi-agent coordination patterns

Output Format

When creating an agent with this skill, I will:

1. Ask clarifying questions:

   • Agent's focused purpose
   • When it should be used
   • Required tools
   • Scope (project/user/plugin)
   • Multi-agent system role

2. Create agent definition with:

   • Valid YAML frontmatter
   • Clear identity and scope
   • Step-by-step workflow
   • Explicit deliverable format
   • NEVER/ALWAYS guardrails
   • Concrete examples

3. Validate against requirements:

   • Frontmatter syntax
   • Tool access (least privilege)
   • Description specificity
   • Context isolation awareness

4. Provide testing instructions:

   • Example trigger queries
   • Expected delegation behavior
   • Verification steps

The result will be a complete, working agent definition following all Anthropic best practices.