gh-coalesce-labs-catalyst-plugins-dev/agents

agents/ Directory: Specialized Research Agents

This directory contains markdown files that define specialized research agents for Claude Code. Agents are invoked by commands using the Task tool to perform focused research tasks in parallel.

How Agents Work

Agents vs Commands:

• Commands (/command-name) - User-facing workflows you invoke directly
• Agents (@catalyst-dev:name) - Specialized research tools spawned by commands

Invocation: Commands spawn agents using the Task tool:

Task(subagent_type="catalyst-dev:codebase-locator", prompt="Find authentication files")

Philosophy: All agents follow a documentarian, not critic approach:

• Document what EXISTS, not what should exist
• NO suggestions for improvements unless explicitly asked
• NO root cause analysis unless explicitly asked
• Focus on answering "WHERE is X?" and "HOW does X work?"

Available Agents

Codebase Research Agents

codebase-locator

Purpose: Find WHERE code lives in a codebase

Use when: You need to locate files, directories, or components

• Finding all files related to a feature
• Discovering directory structure
• Locating test files, configs, or documentation

Tools: Grep, Glob, Bash(ls *)

Example invocation:

Task( subagent_type="catalyst-dev:codebase-locator", prompt="Find all authentication-related files" )

Returns: Organized list of file locations categorized by purpose

---

codebase-analyzer

Purpose: Understand HOW specific code works

Use when: You need to analyze implementation details

• Understanding how a component functions
• Documenting data flow
• Identifying integration points
• Tracing function calls

Tools: Read, Grep, Glob, Bash(ls *)

Example invocation:

Task( subagent_type="catalyst-dev:codebase-analyzer", prompt="Analyze the authentication middleware
implementation and document how it works" )

Returns: Detailed analysis of how code works, with file:line references

---

codebase-pattern-finder

Purpose: Find existing patterns and usage examples

Use when: You need concrete examples

• Finding similar implementations
• Discovering usage patterns
• Locating test examples
• Understanding conventions

Tools: Grep, Glob, Read, Bash(ls *)

Example invocation:

Task( subagent_type="catalyst-dev:codebase-pattern-finder", prompt="Find examples of how other components handle
error logging" )

Returns: Concrete code examples showing patterns in use

Thoughts System Agents

thoughts-locator

Purpose: Discover existing thought documents about a topic

Use when: You need to find related research or plans

• Finding previous research on a topic
• Discovering related plans
• Locating historical decisions
• Searching for related discussions

Tools: Grep, Glob, LS

Example invocation:

Task( subagent_type="catalyst-dev:thoughts-locator", prompt="Find all thoughts documents about authentication" )

Returns: List of relevant thought documents with paths

---

thoughts-analyzer

Purpose: Extract key insights from thought documents

Use when: You need to understand documented decisions

• Analyzing research documents
• Understanding plan rationale
• Extracting historical context
• Identifying previous decisions

Tools: Read, Grep, Glob, LS

Example invocation:

Task( subagent_type="catalyst-dev:thoughts-analyzer", prompt="Analyze the authentication research document and
extract key findings" )

Returns: Summary of insights and decisions from documents

External Research Agents

external-research

Purpose: Research external frameworks and repositories

Use when: You need information from outside sources

• Understanding how popular repos implement features
• Learning framework patterns
• Researching best practices from open-source
• Discovering external documentation

Tools: mcpdeepwikiask_question, mcpdeepwikiread_wiki_structure

Example invocation:

Task( subagent_type="catalyst-dev:external-research", prompt="Research how Next.js implements middleware
authentication patterns" )

Returns: Information from external repositories and documentation

Agent File Structure

Every agent file has this structure:

---
name: agent-name
description: What this agent does
tools: Tool1, Tool2, Tool3
model: inherit
---

# Agent Implementation

Instructions for the agent...

## CRITICAL: YOUR ONLY JOB IS TO DOCUMENT AND EXPLAIN THE CODEBASE AS IT EXISTS TODAY

- DO NOT suggest improvements...
- DO NOT perform root cause analysis...
- ONLY describe what exists...

Required Frontmatter Fields

• name - Agent identifier (matches filename without .md)
• description - One-line description for invoking commands
• tools - Tools available to the agent
• model - AI model to use (usually "inherit")

Naming Convention

• Filename: agent-name.md (hyphen-separated)
• Frontmatter name: agent-name (matches filename)
• Unlike commands, agents MUST have a name field

How Commands Use Agents

Parallel Research Pattern

Commands spawn multiple agents concurrently for efficiency:

# Spawn three agents in parallel

Task(subagent_type="catalyst-dev:codebase-locator", ...) Task(subagent_type="catalyst-dev:thoughts-locator", ...)
Task(subagent_type="catalyst-dev:codebase-analyzer", ...)

# Wait for all to complete

# Synthesize findings

Example from research_codebase.md

Task 1 - Find WHERE components live: subagent: codebase-locator prompt: "Find all files related to
authentication"

Task 2 - Understand HOW it works: subagent: codebase-analyzer prompt: "Analyze auth middleware and
document how it works"

Task 3 - Find existing patterns: subagent: codebase-pattern-finder prompt: "Find similar
authentication implementations"

Documentarian Philosophy

What agents do:

• ✅ Locate files and components
• ✅ Document how code works
• ✅ Provide concrete examples
• ✅ Explain data flow
• ✅ Show integration points

What agents do NOT do:

• ❌ Suggest improvements
• ❌ Critique implementation
• ❌ Identify bugs (unless asked)
• ❌ Recommend refactoring
• ❌ Comment on code quality

Why this matters:

• Research should be objective
• Understanding comes before judgment
• Prevents bias in documentation
• Maintains focus on current state

Plugin Distribution

Agents are distributed as part of the Catalyst plugin system:

Installation

Install Catalyst plugin:

/plugin install catalyst-dev

This installs all agents automatically.

Updates

Update plugin:

/plugin update catalyst-dev

Agents are pure research logic with no project-specific configuration, so updates are always safe.

Per-Project Availability

Agents are available in any project where the catalyst-dev plugin is installed. No per-project setup needed.

Creating New Agents

Step 1: Create Markdown File

# Create file with hyphen-separated name
touch agents/my-new-agent.md

Step 2: Add Frontmatter

---
name: my-new-agent
description: Clear, focused description of what this agent finds or analyzes
tools: Read, Grep, Glob
model: inherit
---

Step 3: Write Agent Logic

You are a specialist at [specific research task].

## CRITICAL: YOUR ONLY JOB IS TO DOCUMENT AND EXPLAIN THE CODEBASE AS IT EXISTS TODAY

[Standard documentarian guidelines]

## Core Responsibilities

1. **[Primary Task]**
   - [Specific action]
   - [What to look for]

2. **[Secondary Task]**
   - [Specific action]
   - [What to document]

## Output Format

[Specify how results should be structured]

Step 4: Test

# In this workspace, agents are immediately available via symlinks
# Just restart Claude Code to reload

# Create a command that uses the agent
# Invoke the command to test the agent

Step 5: Validate Frontmatter

# In Claude Code (workspace only)
/validate-frontmatter

Common Patterns

Pattern 1: Locator → Analyzer

# First, find files

Task(subagent_type="catalyst-dev:codebase-locator", ...)

# Then analyze the most relevant ones

Task(subagent_type="catalyst-dev:codebase-analyzer", ...)

Pattern 2: Parallel Search

# Search codebase and thoughts simultaneously

Task(subagent_type="catalyst-dev:codebase-locator", ...) Task(subagent_type="catalyst-dev:thoughts-locator", ...)

Pattern 3: Pattern Discovery

# Find patterns after understanding the code

Task(subagent_type="catalyst-dev:codebase-analyzer", ...) Task(subagent_type="catalyst-dev:codebase-pattern-finder", ...)

Tool Access

Agents specify required tools in frontmatter:

File Operations:

• Read - Read file contents
• Write - Create files (rare for agents)

Search:

• Grep - Content search
• Glob - File pattern matching

Execution:

• Bash(ls *) - List directory contents

External:

• mcp__deepwiki__ask_question - Query external repos
• mcp__deepwiki__read_wiki_structure - Read external docs

Troubleshooting

Agent not found when spawned

Check:

1. Plugin installed? Run /plugin list to verify
2. Frontmatter name field matches filename?
3. Restarted Claude Code after adding/modifying agent?

Solution:

# Update plugin
/plugin update catalyst-dev

# Restart Claude Code

Agent auto-updated by plugin

This is by design - agents are pure logic with no project-specific config.

If you need customization:

• Don't modify plugin agents - they'll be overwritten on update
• Create a custom agent in .claude/plugins/custom/agents/
• Use a different name to avoid conflicts

See Also

• ../commands/README.md - Documentation for commands in this plugin
• ../../docs/AGENTIC_WORKFLOW_GUIDE.md - Agent patterns and best practices
• ../../docs/FRONTMATTER_STANDARD.md - Frontmatter validation rules
• ../../README.md - Workspace overview
• ../../scripts/README.md - Setup scripts documentation