Agent Development for Claude Code Plugins
Overview
Agents are autonomous subprocesses that handle complex, multi-step tasks independently. Understanding agent structure, triggering conditions, and system prompt design enables creating powerful autonomous capabilities.
Key concepts:
Agents are FOR autonomous work, commands are FOR user-initiated actions
Markdown file format with YAML frontmatter
Triggering via description field with examples
System prompt defines agent behavior
Model and color customization
Agent File Structure
Complete Format
name
:
agent
-
identifier
description
:
Use this agent when
[
triggering conditions
]
. Examples
:
<example
Context
:
[
Situation description
]
user
:
"[User request]"
assistant
:
"[How assistant should respond and use this agent]"
<commentary
[
Why this agent should be triggered
]
</commentary
</example
<example
[
Additional example
...
]
</example
model
:
inherit
color
:
blue
tools
:
[
"Read"
,
"Write"
,
"Grep"
]
You are [agent role description]...
**
Your Core Responsibilities:
**
1.
[Responsibility 1]
2.
[Responsibility 2]
**
Analysis Process:
**
[Step-by-step workflow]
**
Output Format:
**
[What to return]
Frontmatter Fields
name (required)
Agent identifier used for namespacing and invocation.
Format:
lowercase, numbers, hyphens only
Length:
3-50 characters
Pattern:
Must start and end with alphanumeric
Good examples:
code-reviewer
test-generator
api-docs-writer
security-analyzer
Bad examples:
helper
(too generic)
-agent-
(starts/ends with hyphen)
my_agent
(underscores not allowed)
ag
(too short, < 3 chars)
description (required)
Defines when Claude should trigger this agent.
This is the most critical field.
Must include:
Triggering conditions ("Use this agent when...")
Multiple
blocks showing usage
Context, user request, and assistant response in each example
explaining why agent triggers
Format:
Use this agent when [conditions]. Examples:
Context: [Scenario description]
user: "[What user says]"
assistant: "[How Claude should respond]"
[Why this agent is appropriate]
[More examples...]
Best practices:
Include 2-4 concrete examples
Show proactive and reactive triggering
Cover different phrasings of same intent
Explain reasoning in commentary
Be specific about when NOT to use the agent
model (required)
Which model the agent should use.
Options:
inherit
- Use same model as parent (recommended)
sonnet
- Claude Sonnet (balanced)
opus
- Claude Opus (most capable, expensive)
haiku
- Claude Haiku (fast, cheap)
Recommendation:
Use
inherit
unless agent needs specific model capabilities.
color (required)
Visual identifier for agent in UI.
Options:
blue
,
cyan
,
green
,
yellow
,
magenta
,
red
Guidelines:
Choose distinct colors for different agents in same plugin
Use consistent colors for similar agent types
Blue/cyan: Analysis, review
Green: Success-oriented tasks
Yellow: Caution, validation
Red: Critical, security
Magenta: Creative, generation
tools (optional)
Restrict agent to specific tools.
Format:
Array of tool names
tools
:
[
"Read"
,
"Write"
,
"Grep"
,
"Bash"
]
Default:
If omitted, agent has access to all tools
Best practice:
Limit tools to minimum needed (principle of least privilege)
Common tool sets:
Read-only analysis:
["Read", "Grep", "Glob"]
Code generation:
["Read", "Write", "Grep"]
Testing:
["Read", "Bash", "Grep"]
Full access: Omit field or use
["*"]
System Prompt Design
The markdown body becomes the agent's system prompt. Write in second person, addressing the agent directly.
Structure
Standard template:
You are [role] specializing in [domain].
**
Your Core Responsibilities:
**
1.
[Primary responsibility]
2.
[Secondary responsibility]
3.
[Additional responsibilities...]
**
Analysis Process:
**
1.
[Step one]
2.
[Step two]
3.
[Step three]
[...]
**
Quality Standards:
**
-
[Standard 1]
-
[Standard 2]
**
Output Format:
**
Provide results in this format:
-
[What to include]
-
[How to structure]
**
Edge Cases:
**
Handle these situations:
-
[
Edge case 1
]
:
[How
to handle]
-
[
Edge case 2
]
:
[How
to handle]
Best Practices
✅
DO:
Write in second person ("You are...", "You will...")
Be specific about responsibilities
Provide step-by-step process
Define output format
Include quality standards
Address edge cases
Keep under 10,000 characters
❌
DON'T:
Write in first person ("I am...", "I will...")
Be vague or generic
Omit process steps
Leave output format undefined
Skip quality guidance
Ignore error cases
Creating Agents
Method 1: AI-Assisted Generation
Use this prompt pattern (extracted from Claude Code):
Create an agent configuration based on this request: "[YOUR DESCRIPTION]"
Requirements:
1. Extract core intent and responsibilities
2. Design expert persona for the domain
3. Create comprehensive system prompt with:
- Clear behavioral boundaries
- Specific methodologies
- Edge case handling
- Output format
4. Create identifier (lowercase, hyphens, 3-50 chars)
5. Write description with triggering conditions
6. Include 2-3 blocks showing when to use
Return JSON with:
{
"identifier": "agent-name",
"whenToUse": "Use this agent when... Examples: ...",
"systemPrompt": "You are..."
}
Then convert to agent file format with frontmatter.
See
examples/agent-creation-prompt.md
for complete template.
Method 2: Manual Creation
Choose agent identifier (3-50 chars, lowercase, hyphens)
Write description with examples
Select model (usually
inherit
)
Choose color for visual identification
Define tools (if restricting access)
Write system prompt with structure above
Save as
agents/agent-name.md
Validation Rules
Identifier Validation
✅ Valid: code-reviewer, test-gen, api-analyzer-v2
❌ Invalid: ag (too short), -start (starts with hyphen), my_agent (underscore)
Rules:
3-50 characters
Lowercase letters, numbers, hyphens only
Must start and end with alphanumeric
No underscores, spaces, or special characters
Description Validation
Length:
10-5,000 characters
Must include:
Triggering conditions and examples
Best:
200-1,000 characters with 2-4 examples
System Prompt Validation
Length:
20-10,000 characters
Best:
500-3,000 characters
Structure:
Clear responsibilities, process, output format
Agent Organization
Plugin Agents Directory
plugin-name/
└── agents/
├── analyzer.md
├── reviewer.md
└── generator.md
All
.md
files in
agents/
are auto-discovered.
Namespacing
Agents are namespaced automatically:
Single plugin:
agent-name
With subdirectories:
plugin:subdir:agent-name
Testing Agents
Test Triggering
Create test scenarios to verify agent triggers correctly:
Write agent with specific triggering examples
Use similar phrasing to examples in test
Check Claude loads the agent
Verify agent provides expected functionality
Test System Prompt
Ensure system prompt is complete:
Give agent typical task
Check it follows process steps
Verify output format is correct
Test edge cases mentioned in prompt
Confirm quality standards are met
Quick Reference
Minimal Agent
name
:
simple
-
agent
description
:
Use this agent when... Examples
:
<example
...
</example
model
:
inherit
color
:
blue
You are an agent that [does X].
Process:
1.
[Step 1]
2.
[Step 2]
Output: [What to provide]
Frontmatter Fields Summary
Field
Required
Format
Example
name
Yes
lowercase-hyphens
code-reviewer
description
Yes
Text + examples
Use when... ...
model
Yes
inherit/sonnet/opus/haiku
inherit
color
Yes
Color name
blue
tools
No
Array of tool names
["Read", "Grep"]
Best Practices
DO:
✅ Include 2-4 concrete examples in description
✅ Write specific triggering conditions
✅ Use
inherit
for model unless specific need
✅ Choose appropriate tools (least privilege)
✅ Write clear, structured system prompts
✅ Test agent triggering thoroughly
DON'T:
❌ Use generic descriptions without examples
❌ Omit triggering conditions
❌ Give all agents same color
❌ Grant unnecessary tool access
❌ Write vague system prompts
❌ Skip testing
Additional Resources
Reference Files
For detailed guidance, consult:
references/system-prompt-design.md
- Complete system prompt patterns
references/triggering-examples.md
- Example formats and best practices
references/agent-creation-system-prompt.md
- The exact prompt from Claude Code
Example Files
Working examples in
examples/
:
agent-creation-prompt.md
- AI-assisted agent generation template
complete-agent-examples.md
- Full agent examples for different use cases
Utility Scripts
Development tools in
scripts/
:
validate-agent.sh
- Validate agent file structure
test-agent-trigger.sh
- Test if agent triggers correctly
Implementation Workflow
To create an agent for a plugin:
Define agent purpose and triggering conditions
Choose creation method (AI-assisted or manual)
Create
agents/agent-name.md
file
Write frontmatter with all required fields
Write system prompt following best practices
Include 2-4 triggering examples in description
Validate with
scripts/validate-agent.sh
Test triggering with real scenarios
Document agent in plugin README
Focus on clear triggering conditions and comprehensive system prompts for autonomous operation.