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feat(agents): dogfood dev-agent MCP tools in Claude agents
Give our own agents access to the MCP tools they build and maintain.
Each agent gets the tools most relevant to its workflow — semantic
search for investigators, ref tracing for reviewers, pattern analysis
for quality checks.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Copy file name to clipboardExpand all lines: .claude/agents/bug-investigator.md
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---
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name: bug-investigator
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description: "Traces bugs through the codebase and identifies root causes. Use when debugging issues, investigating errors, or understanding why something is broken."
Systematically traces issues through the dev-agent monorepo. Reproduces, traces, fixes, and prevents regression.
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## MCP Tools — Use These First
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-**`dev_search`** — Start here for any conceptual query ("where does rate limiting happen", "how are embeddings stored"). Semantic search finds code by meaning, not just keywords.
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-**`dev_refs`** — Trace callers/callees of a function to map the data flow. Use this instead of grepping for function names when tracing how data moves across packages.
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-**`dev_map`** — Check change frequency to see what files changed recently. Useful for "when did it break?" — high-churn files near the bug timeframe are prime suspects.
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Fall back to Grep/Glob for exact string matches or file patterns.
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## Investigation Framework
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### Phase 1: Understand the Bug
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1. What is the expected behavior?
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2. What is the actual behavior?
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3. What are the reproduction steps?
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4. When did it start happening? (check recent commits)
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4. When did it start happening? (check recent commits + `dev_map` for churn)
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5. Is it consistent or intermittent?
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### Phase 2: Trace the Data Flow
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Use `dev_refs` to trace caller/callee chains along these paths:
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**MCP path:**
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```
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AI Tool Request → MCP Server → Adapter → Core Service → Scanner/Vector/GitHub
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### Phase 3: Identify Root Cause
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Use `dev_search` to find code related to each symptom area:
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| Symptom | Likely Cause | Where to Look |
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|---------|--------------|---------------|
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| MCP tool returns empty | Index not built or stale |`packages/core/src/indexer/`|
-[ ] Core exports consumed correctly by CLI, MCP server, and subagents
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Use `dev_refs` to trace caller/callee chains across package boundaries. Use `dev_search` to find related code by concept when the function name isn't obvious.
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-[ ] Core exports consumed correctly by CLI, MCP server, and subagents — verify with `dev_refs`
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-[ ] Type boundaries between packages match (no `any` casting to bridge mismatches)
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-[ ] Logger (@prosdevlab/kero) configuration consistent across consumers
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-[ ] Use `dev_patterns` to check if error handling patterns are consistent with existing code
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### Pass 1: Engineer Review
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Read the plan as a senior engineer. Check:
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Read the plan as a senior engineer. Use `dev_map` to verify structure claims, `dev_refs` to confirm dependency assertions, and `dev_patterns` to check if proposed patterns match existing conventions.
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1.**Context** — Does it accurately describe what exists today? (Verify by reading the actual code)
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1.**Context** — Does it accurately describe what exists today? (Verify with `dev_map` and reading actual code)
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2.**Architecture** — Does the proposed design fit the existing monorepo structure?
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3.**Parts breakdown** — Are parts sized correctly? (Each should be 1-2 commits)
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4.**Dependencies** — Are cross-package dependencies identified?
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4.**Dependencies** — Are cross-package dependencies identified? (Verify with `dev_refs`)
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5.**Build order** — Does the implementation order respect the build dependency chain?
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6.**Breaking changes** — Are they identified and migration paths described?
Use `dev_map` to understand the structural impact of changes and identify which areas of the codebase were modified. Use `dev_status` to verify the index is healthy before PR.
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-[ ] MCP adapters follow the adapter pattern consistently
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### Readability & Simplification
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-[ ] No code duplicating existing utilities
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Use `dev_patterns` to find similar code and detect duplication. Use `dev_search` to check if a utility already exists before flagging missing abstractions.
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-[ ] No code duplicating existing utilities — verify with `dev_patterns` and `dev_search`
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-[ ] Functions reasonably sized (consider splitting if >50 lines)
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-[ ] Complex logic has comments explaining "why", not "what"
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-[ ] No premature abstractions for one-time operations
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## Workflow
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1.**Search** — Use Glob for file patterns, Grep for content
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2.**Verify** — Read the file to confirm the match
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3.**Report** — Concise, factual answer with file paths and line numbers
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1.**Search** — Start with `dev_search` for conceptual queries ("authentication flow", "error handling"). Fall back to Grep for exact string matches and Glob for file patterns.
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2.**Trace** — Use `dev_refs` to find callers/callees when tracing usage across packages. Faster and more complete than grepping for function names.
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3.**Map** — Use `dev_map` when asked about codebase structure or to identify high-churn areas.
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4.**Verify** — Read the file to confirm the match
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5.**Report** — Concise, factual answer with file paths and line numbers
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This agent **NEVER writes code**. It produces investigation plans.
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## MCP Tools — Use These to Map the Territory
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-**`dev_search`** — Find relevant code areas by meaning. Start broad ("authentication middleware", "vector storage") to discover what exists before diving in.
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-**`dev_map`** — Get codebase structure with change frequency. Use early to understand scope and identify hot spots.
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-**`dev_patterns`** — Analyze existing patterns before proposing new ones. Find similar implementations, error handling conventions, and type patterns.
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-**`dev_refs`** — Trace cross-package dependencies. Understand what depends on what before proposing changes.
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## When to Use
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- Before starting a feature that touches unfamiliar parts of the codebase
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## Workflow
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1.**Clarify the goal** — What are we trying to understand or achieve?
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2.**Map the territory** — What parts of the codebase are relevant?
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2.**Map the territory** — Use `dev_map` for structure, `dev_search` to find relevant areas, `dev_patterns` to understand conventions
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3.**Identify unknowns** — What do we need to learn before proceeding?
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4.**Plan the investigation** — Ordered steps with specific files/functions to examine
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5.**Estimate scope** — How big is this? Should we break it down?
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4.**Trace dependencies** — Use `dev_refs` to understand cross-package impact
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5.**Plan the investigation** — Ordered steps with specific files/functions to examine
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6.**Estimate scope** — How big is this? Should we break it down?
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## Checklist
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Use `dev_search` to find security-sensitive code ("user input", "shell execution", "token handling"). Use `dev_patterns` to find similar patterns across the codebase — if one injection vector exists, the same pattern likely appears elsewhere. Use `dev_refs` to trace how user input flows through the system.
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### Command Injection
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-[ ] No unsanitized user input passed to `child_process`, `exec`, `execSync`, or shell commands
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-[ ] GitHub CLI calls (`gh`) use parameterized arguments, not string interpolation
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