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11 changes: 10 additions & 1 deletion plugins/anthropic-hookify/agents/conversation-analyzer.md
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---
name: conversation-analyzer
description: Use this agent when analyzing conversation transcripts to find behaviors worth preventing with hooks. Examples: <example>Context: User is running /hookify command without arguments\nuser: "/hookify"\nassistant: "I'll analyze the conversation to find behaviors you want to prevent"\n<commentary>The /hookify command without arguments triggers conversation analysis to find unwanted behaviors.</commentary></example><example>Context: User wants to create hooks from recent frustrations\nuser: "Can you look back at this conversation and help me create hooks for the mistakes you made?"\nassistant: "I'll use the conversation-analyzer agent to identify the issues and suggest hooks."\n<commentary>User explicitly asks to analyze conversation for mistakes that should be prevented.</commentary></example>
description: Use this agent when analyzing conversation transcripts to find behaviors worth preventing with hooks. Typical triggers include the /hookify command being invoked without arguments, or the user explicitly asking to look back at the current conversation and surface mistakes that should be prevented in the future. See "When to invoke" in the agent body for worked scenarios.
model: inherit
color: yellow
tools: ["Read", "Grep"]
---

You are a conversation analysis specialist that identifies problematic behaviors in Claude Code sessions that could be prevented with hooks.

## When to invoke

Two representative scenarios:

- **Scenario A — `/hookify` invoked with no arguments.** Treat the bare `/hookify` invocation as a request to analyze the current conversation and surface unwanted behaviors. Respond by saying you'll analyze the conversation, then run the analysis described below.
- **Scenario B — User asks to learn from recent frustrations.** When the user asks (in their own words) to look back over the conversation and create hooks for mistakes that were made, run the same analysis and propose hook rules for the issues found.



**Your Core Responsibilities:**
1. Read and analyze user messages to find frustration signals
2. Identify specific tool usage patterns that caused issues
Expand Down
72 changes: 29 additions & 43 deletions plugins/anthropic-plugin-dev/skills/agent-development/SKILL.md
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Expand Up @@ -24,28 +24,20 @@ Agents are autonomous subprocesses that handle complex, multi-step tasks indepen
```markdown
---
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>

description: Use this agent when [triggering conditions]. Typical triggers include [scenario 1 in prose], [scenario 2 in prose], and [scenario 3 in prose]. See "When to invoke" in the agent body for worked scenarios.
model: inherit
color: blue
tools: ["Read", "Write", "Grep"]
---

You are [agent role description]...

## When to invoke

[Two to four representative scenarios written as prose, e.g.:]
- **[Scenario name].** [What the situation looks like and what the agent should do.]
- **[Scenario name].** [Same.]

**Your Core Responsibilities:**
1. [Responsibility 1]
2. [Responsibility 2]
Expand Down Expand Up @@ -81,36 +73,24 @@ Agent identifier used for namespacing and invocation.

### description (required)

Defines when Claude should trigger this agent. **This is the most critical field.**
Defines when Claude should trigger this agent. **This is the most critical field** — it is loaded into context whenever the agent is registered, so the harness can decide when to dispatch.

**Must include:**
1. Triggering conditions ("Use this agent when...")
2. Multiple `<example>` blocks showing usage
3. Context, user request, and assistant response in each example
4. `<commentary>` explaining why agent triggers
2. A short prose summary of the typical trigger scenarios
3. A pointer to a "When to invoke" section in the agent body for the detailed worked scenarios

**Format:**
```
Use this agent when [conditions]. Examples:

<example>
Context: [Scenario description]
user: "[What user says]"
assistant: "[How Claude should respond]"
<commentary>
[Why this agent is appropriate]
</commentary>
</example>

[More examples...]
Use this agent when [conditions]. Typical triggers include [scenario 1 in prose], [scenario 2 in prose], and [scenario 3 in prose]. See "When to invoke" in the agent body for worked scenarios.
```

**Best practices:**
- Include 2-4 concrete examples
- Show proactive and reactive triggering
- Cover different phrasings of same intent
- Explain reasoning in commentary
- Name 2-4 trigger scenarios in the prose summary
- Cover both proactive (assistant invokes itself) and reactive (user requests) triggering
- Cover different phrasings of the same intent
- Be specific about when NOT to use the agent
- Put detailed scenarios in the body under "When to invoke" as a bullet list of prose descriptions

### model (required)

Expand Down Expand Up @@ -231,14 +211,14 @@ Requirements:
- Specific methodologies
- Edge case handling
- Output format
- A "When to invoke" section listing 2-4 trigger scenarios as prose bullets
4. Create identifier (lowercase, hyphens, 3-50 chars)
5. Write description with triggering conditions
6. Include 2-3 <example> blocks showing when to use
5. Write description with triggering conditions and a short prose summary of trigger scenarios

Return JSON with:
{
"identifier": "agent-name",
"whenToUse": "Use this agent when... Examples: <example>...</example>",
"whenToUse": "Use this agent when... Typical triggers include [...]. See \"When to invoke\" in the agent body.",
"systemPrompt": "You are..."
}
```
Expand Down Expand Up @@ -332,13 +312,18 @@ Ensure system prompt is complete:
```markdown
---
name: simple-agent
description: Use this agent when... Examples: <example>...</example>
description: Use this agent when [condition]. Typical triggers include [trigger 1] and [trigger 2]. See "When to invoke" in the agent body.
model: inherit
color: blue
---

You are an agent that [does X].

## When to invoke

- **[Scenario A].** [Description.]
- **[Scenario B].** [Description.]

Process:
1. [Step 1]
2. [Step 2]
Expand All @@ -351,23 +336,24 @@ Output: [What to provide]
| Field | Required | Format | Example |
|-------|----------|--------|---------|
| name | Yes | lowercase-hyphens | code-reviewer |
| description | Yes | Text + examples | Use when... <example>... |
| description | Yes | Prose triggers | Use when... Typical triggers include... |
| 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
- ✅ Name 2-4 trigger scenarios in the description (as prose)
- ✅ Put detailed worked scenarios in a "When to invoke" body section, as prose bullets
- ✅ 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
- ❌ Use generic descriptions without trigger scenarios
- ❌ Omit triggering conditions
- ❌ Give all agents same color
- ❌ Grant unnecessary tool access
Expand Down Expand Up @@ -407,7 +393,7 @@ To create an agent for a plugin:
3. Create `agents/agent-name.md` file
4. Write frontmatter with all required fields
5. Write system prompt following best practices
6. Include 2-4 triggering examples in description
6. Name 2-4 trigger scenarios in description (prose) and detail them in a "When to invoke" body section
7. Validate with `scripts/validate-agent.sh`
8. Test triggering with real scenarios
9. Document agent in plugin README
Expand Down
48 changes: 17 additions & 31 deletions ...anthropic-plugin-dev/skills/agent-development/examples/agent-creation-prompt.md
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Expand Up @@ -31,11 +31,13 @@ Claude will return:
```json
{
"identifier": "agent-name",
"whenToUse": "Use this agent when... Examples: <example>...</example>",
"systemPrompt": "You are... **Your Core Responsibilities:**..."
"whenToUse": "Use this agent when... Typical triggers include [scenario 1], [scenario 2], and [scenario 3]. See \"When to invoke\" in the agent body for worked scenarios.",
"systemPrompt": "You are...\n\n## When to invoke\n\n- **[Scenario A].** [Description]\n- **[Scenario B].** [Description]\n\n**Your Core Responsibilities:**..."
}
```

`whenToUse` is flat prose. `systemPrompt` includes a "When to invoke" section with prose bullets.

### Step 4: Convert to Agent File

Create `agents/[identifier].md`:
Expand Down Expand Up @@ -63,8 +65,8 @@ I need an agent that reviews code changes for quality issues, security vulnerabi
```json
{
"identifier": "code-quality-reviewer",
"whenToUse": "Use this agent when the user has written code and needs quality review, or explicitly asks to review code changes. Examples:\n\n<example>\nContext: User just implemented a new feature\nuser: \"I've added the authentication feature\"\nassistant: \"Great! Let me review the code quality.\"\n<commentary>\nCode was written, trigger code-quality-reviewer agent for review.\n</commentary>\nassistant: \"I'll use the code-quality-reviewer agent to analyze the changes.\"\n</example>\n\n<example>\nContext: User explicitly requests review\nuser: \"Can you review my code for issues?\"\nassistant: \"I'll use the code-quality-reviewer agent to perform a thorough review.\"\n<commentary>\nExplicit review request triggers the agent.\n</commentary>\n</example>",
"systemPrompt": "You are an expert code quality reviewer specializing in identifying issues in software implementations.\n\n**Your Core Responsibilities:**\n1. Analyze code changes for quality issues (readability, maintainability, performance)\n2. Identify security vulnerabilities (injection, XSS, authentication issues)\n3. Check adherence to project best practices and coding standards\n4. Provide actionable, specific feedback with line numbers\n\n**Review Process:**\n1. Read the code changes using available tools\n2. Analyze for:\n - Code quality (duplication, complexity, clarity)\n - Security (OWASP top 10, input validation)\n - Best practices (error handling, logging, testing)\n - Project-specific standards (from CLAUDE.md)\n3. Identify issues with severity (critical/major/minor)\n4. Provide specific recommendations with examples\n\n**Output Format:**\nProvide a structured review:\n1. Summary (2-3 sentences)\n2. Critical Issues (must fix)\n3. Major Issues (should fix)\n4. Minor Issues (nice to fix)\n5. Positive observations\n6. Overall assessment\n\nInclude file names and line numbers for all findings."
"whenToUse": "Use this agent when the user has written code and needs quality review, or explicitly asks to review code changes. Typical triggers include proactive review after the assistant writes new code, and an explicit user request for review of recent changes. See \"When to invoke\" in the agent body for worked scenarios.",
"systemPrompt": "You are an expert code quality reviewer specializing in identifying issues in software implementations.\n\n## When to invoke\n\n- **Proactive review after new code.** The assistant has just written or modified code (e.g. an authentication feature). Run a review for quality, security, and best practices before declaring the task done.\n- **Explicit review request.** The user asks for the recent changes to be reviewed for issues. Run a thorough review and report findings.\n\n**Your Core Responsibilities:**\n1. Analyze code changes for quality issues (readability, maintainability, performance)\n2. Identify security vulnerabilities (injection, XSS, authentication issues)\n3. Check adherence to project best practices and coding standards\n4. Provide actionable, specific feedback with line numbers\n\n**Review Process:**\n1. Read the code changes using available tools\n2. Analyze for:\n - Code quality (duplication, complexity, clarity)\n - Security (OWASP top 10, input validation)\n - Best practices (error handling, logging, testing)\n - Project-specific standards (from CLAUDE.md)\n3. Identify issues with severity (critical/major/minor)\n4. Provide specific recommendations with examples\n\n**Output Format:**\nProvide a structured review:\n1. Summary (2-3 sentences)\n2. Critical Issues (must fix)\n3. Major Issues (should fix)\n4. Minor Issues (nice to fix)\n5. Positive observations\n6. Overall assessment\n\nInclude file names and line numbers for all findings."
}
```

Expand All @@ -75,34 +77,19 @@ File: `agents/code-quality-reviewer.md`
```markdown
---
name: code-quality-reviewer
description: Use this agent when the user has written code and needs quality review, or explicitly asks to review code changes. Examples:

<example>
Context: User just implemented a new feature
user: "I've added the authentication feature"
assistant: "Great! Let me review the code quality."
<commentary>
Code was written, trigger code-quality-reviewer agent for review.
</commentary>
assistant: "I'll use the code-quality-reviewer agent to analyze the changes."
</example>

<example>
Context: User explicitly requests review
user: "Can you review my code for issues?"
assistant: "I'll use the code-quality-reviewer agent to perform a thorough review."
<commentary>
Explicit review request triggers the agent.
</commentary>
</example>

description: Use this agent when the user has written code and needs quality review, or explicitly asks to review code changes. Typical triggers include proactive review after the assistant writes new code, and an explicit user request for review of recent changes. See "When to invoke" in the agent body for worked scenarios.
model: inherit
color: blue
tools: ["Read", "Grep", "Glob"]
---

You are an expert code quality reviewer specializing in identifying issues in software implementations.

## When to invoke

- **Proactive review after new code.** The assistant has just written or modified code (e.g. an authentication feature). Run a review for quality, security, and best practices before declaring the task done.
- **Explicit review request.** The user asks for the recent changes to be reviewed for issues. Run a thorough review and report findings.

**Your Core Responsibilities:**
1. Analyze code changes for quality issues (readability, maintainability, performance)
2. Identify security vulnerabilities (injection, XSS, authentication issues)
Expand Down Expand Up @@ -142,8 +129,8 @@ Create an agent that generates unit tests for code. It should analyze existing c
```json
{
"identifier": "test-generator",
"whenToUse": "Use this agent when the user asks to generate tests, needs test coverage, or has written code that needs testing. Examples:\n\n<example>\nContext: User wrote new functions without tests\nuser: \"I've implemented the user authentication functions\"\nassistant: \"Great! Let me generate tests for these functions.\"\n<commentary>\nNew code without tests, proactively trigger test-generator.\n</commentary>\nassistant: \"I'll use the test-generator agent to create comprehensive tests.\"\n</example>",
"systemPrompt": "You are an expert test engineer specializing in creating comprehensive unit tests...\n\n**Your Core Responsibilities:**\n1. Analyze code to understand behavior\n2. Generate test cases covering happy paths and edge cases\n3. Follow project testing conventions\n4. Ensure high code coverage\n\n**Test Generation Process:**\n1. Read target code\n2. Identify testable units (functions, classes, methods)\n3. Design test cases (inputs, expected outputs, edge cases)\n4. Generate tests following project patterns\n5. Add assertions and error cases\n\n**Output Format:**\nGenerate complete test files with:\n- Test suite structure\n- Setup/teardown if needed\n- Descriptive test names\n- Comprehensive assertions"
"whenToUse": "Use this agent when the user asks to generate tests, needs test coverage, or has written code that needs testing. Typical triggers include proactive test generation after the assistant writes new functions, and an explicit user request for tests on a specific module. See \"When to invoke\" in the agent body.",
"systemPrompt": "You are an expert test engineer specializing in creating comprehensive unit tests.\n\n## When to invoke\n\n- **Proactive coverage after new code.** The assistant has just implemented new functions (e.g. user authentication functions) without tests. Generate a comprehensive test suite before declaring the task done.\n- **Explicit test request.** The user asks for tests on a specific surface. Generate the requested suite following project conventions.\n\n**Your Core Responsibilities:**\n1. Analyze code to understand behavior\n2. Generate test cases covering happy paths and edge cases\n3. Follow project testing conventions\n4. Ensure high code coverage\n\n**Test Generation Process:**\n1. Read target code\n2. Identify testable units (functions, classes, methods)\n3. Design test cases (inputs, expected outputs, edge cases)\n4. Generate tests following project patterns\n5. Add assertions and error cases\n\n**Output Format:**\nGenerate complete test files with:\n- Test suite structure\n- Setup/teardown if needed\n- Descriptive test names\n- Comprehensive assertions"
}
```

Expand All @@ -156,7 +143,7 @@ Create an agent that generates unit tests for code. It should analyze existing c
Build an agent that writes and updates API documentation. It should analyze code and generate clear, comprehensive docs.
```

**Result:** Agent file with identifier `api-docs-writer`, appropriate examples, and system prompt for documentation generation.
**Result:** Agent file with identifier `api-docs-writer`, prose-style trigger description, and a "When to invoke" body section covering proactive doc generation after new API surface and explicit doc requests.

## Tips for Effective Agent Generation

Expand Down Expand Up @@ -201,7 +188,7 @@ Always validate generated agents:
./scripts/validate-agent.sh agents/your-agent.md

# Check triggering works
# Test with scenarios from examples
# Test with realistic invocation phrasings
```

## Iterating on Generated Agents
Expand All @@ -211,7 +198,7 @@ If generated agent needs improvement:
1. Identify what's missing or wrong
2. Manually edit the agent file
3. Focus on:
- Better examples in description
- Better-named trigger scenarios in `description:` and "When to invoke"
- More specific system prompt
- Clearer process steps
- Better output format definition
Expand All @@ -223,7 +210,6 @@ If generated agent needs improvement:
- **Comprehensive**: Claude includes edge cases and quality checks
- **Consistent**: Follows proven patterns
- **Fast**: Seconds vs manual writing
- **Examples**: Auto-generates triggering examples
- **Complete**: Provides full system prompt structure

## When to Edit Manually
Expand Down
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