# Agent Types > Choose the right agent type for each task including built-in agents (Bash, Explore, Plan, general-purpose) and plugin agents (review, research, refactoring, SDLC). Use when selecting agent types, understanding agent capabilities, or matching agents to tasks. Use when this capability is needed. - Skill: `tomevault-io/agent-types` (Agent Skill, multi-file: 2 files) - Install (CLI): `npx skillmds@latest add tomevault-io/agent-types` - Raw SKILL.md: https://api.skillmd.com/api/skills/tomevault-io/agent-types/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: AI & ML - Author: tomevault-io (https://skillmd.com/u/tomevault-io) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/tomevault-io/agent-types --- # Agent Types > **Experimental**: Agent teams are disabled by default. Enable with `CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS` in your [settings.json](https://code.claude.com/docs/en/settings) or environment. Choose the right agent type for each role in your team. Agent types determine what tools are available and what the agent is optimized for. **Related skills:** - [Orchestrating](../orchestrating/SKILL.md) - Primitives overview and quick reference - [Team Management](../team-management/SKILL.md) - Spawning agents into teams - [Orchestration Patterns](../orchestration-patterns/SKILL.md) - Patterns that combine different agent types --- ## Agent Type Selection Guide | Need | Agent Type | Why | |------|-----------|-----| | Search/read code | **Explore** | Read-only, fast, cheap (haiku) | | Architecture design | **Plan** | Read-only, thoughtful analysis | | Run commands/git | **Bash** | Shell access only | | Multi-step implementation | **general-purpose** | Full tool access | | Claude Code questions | **claude-code-guide** | Docs and web access | | Security review | **sdlc:security-reviewer** | Vulnerability assessment, secure coding | | Code quality review | **sdlc:quality-enforcer** | Formatting, linting, code style | | Code simplification | **code-simplifier:code-simplifier** | Clarity, consistency, minimalism | | Architecture analysis | **refactor:architect** | Design review, optimization planning | | Best practices research | **adr:adr-researcher** | Codebase analysis + web research | | Deep code exploration | **feature-dev:code-explorer** | Trace execution paths, map architecture | | Code review | **feature-dev:code-reviewer** | Bugs, logic errors, conventions | | Source code chunk analysis | **swarm:rlm-code-analyzer** | Code-aware, scope context, analysis focus | | Data/CSV chunk analysis | **swarm:rlm-data-analyzer** | Column-aware, distributions, statistics | | JSON chunk analysis | **swarm:rlm-json-analyzer** | Schema-aware, structural patterns | | General chunk-level analysis | **swarm:rlm-chunk-analyzer** | Haiku, fast, structured JSON output | | Synthesize chunk findings | **swarm:rlm-synthesizer** | Sonnet, aggregation and deduplication | **Key rule:** Match the agent's tool access to the task requirements. Read-only agents (Explore, Plan) **cannot** edit or write files. Never assign them implementation work. --- ## Built-in Agent Types These are always available without plugins: ### Bash ```javascript Task({ subagent_type: "Bash", description: "Run git commands", prompt: "Check git status and show recent commits" }) ``` - **Tools:** Bash only - **Model:** Inherits from parent - **Best for:** Git operations, command execution, system tasks ### Explore ```javascript Task({ subagent_type: "Explore", description: "Find API endpoints", prompt: "Find all API endpoints in this codebase. Be very thorough.", model: "haiku" // Fast and cheap }) ``` - **Tools:** All read-only tools (no Edit, Write, NotebookEdit, Task) - **Model:** Haiku (optimized for speed) - **Best for:** Codebase exploration, file searches, code understanding - **Thoroughness levels:** "quick", "medium", "very thorough" ### Plan ```javascript Task({ subagent_type: "Plan", description: "Design auth system", prompt: "Create an implementation plan for adding OAuth2 authentication" }) ``` - **Tools:** All read-only tools - **Model:** Inherits from parent - **Best for:** Architecture planning, implementation strategies ### general-purpose ```javascript Task({ subagent_type: "general-purpose", description: "Research and implement", prompt: "Research React Query best practices and implement caching for the user API" }) ``` - **Tools:** All tools (*) - **Model:** Inherits from parent - **Best for:** Multi-step tasks, research + action combinations ### claude-code-guide ```javascript Task({ subagent_type: "claude-code-guide", description: "Help with Claude Code", prompt: "How do I configure MCP servers?" }) ``` - **Tools:** Read-only + WebFetch + WebSearch - **Best for:** Questions about Claude Code, Agent SDK, Anthropic API ### statusline-setup ```javascript Task({ subagent_type: "statusline-setup", description: "Configure status line", prompt: "Set up a status line showing git branch and node version" }) ``` - **Tools:** Read, Edit only - **Model:** Sonnet - **Best for:** Configuring Claude Code status line --- ## Plugin Agent Types Installed plugins provide specialized agent types grouped by function. > **Plugin Agent Constraints:** Some agent frontmatter fields are **silently ignored** when running as plugin agents (for security reasons). Do not rely on these in plugin agent definitions: > - `hooks` — ignored (cannot execute arbitrary shell commands from plugins) > - `mcpServers` — ignored (MCP server injection not permitted from plugins) > - `permissionMode` — ignored (permission escalation from plugins is blocked) > > Fields that **are** supported in plugin agents: `name`, `description`, `tools`, `disallowedTools`, `model`, `maxTurns`, `skills`, `memory`, `background`, `isolation`. ### Review Agents ```javascript // Security review Task({ subagent_type: "sdlc:security-reviewer", description: "Security audit", prompt: "Audit this PR for security vulnerabilities" }) // Code quality Task({ subagent_type: "sdlc:quality-enforcer", description: "Quality check", prompt: "Check formatting, linting, and code style" }) // Code review (bugs, logic, conventions) Task({ subagent_type: "feature-dev:code-reviewer", description: "Code review", prompt: "Review this code for bugs, logic errors, and adherence to project conventions" }) // Code simplification Task({ subagent_type: "code-simplifier:code-simplifier", description: "Simplicity check", prompt: "Check if this implementation can be simplified" }) // Architecture review Task({ subagent_type: "refactor:architect", description: "Architecture review", prompt: "Review the system architecture of the authentication module" }) // SDLC compliance audit Task({ subagent_type: "sdlc:compliance-auditor", description: "Compliance audit", prompt: "Audit this project against all SDLC standards" }) ``` **All review agents:** - `sdlc:security-reviewer` - Vulnerability assessment, supply chain security, secure coding - `sdlc:quality-enforcer` - Formatting, linting, error handling, documentation standards - `sdlc:compliance-auditor` - Full SDLC compliance audit - `feature-dev:code-reviewer` - Bugs, logic errors, security, code quality, conventions - `code-simplifier:code-simplifier` - Clarity, consistency, minimalism - `refactor:architect` - Architectural analysis, optimization planning - `human-voice:voice-reviewer` - Content voice and tone review ### Research Agents ```javascript // Best practices and architectural research Task({ subagent_type: "adr:adr-researcher", description: "Research auth best practices", prompt: "Research current best practices for JWT authentication" }) // Deep codebase exploration Task({ subagent_type: "feature-dev:code-explorer", description: "Analyze auth module", prompt: "Trace execution paths and map the architecture of the authentication module" }) // Feature architecture design Task({ subagent_type: "feature-dev:code-architect", description: "Design feature architecture", prompt: "Design the architecture for adding OAuth2 authentication based on existing patterns" }) ``` **All research agents:** - `adr:adr-researcher` - Codebase analysis + web search for best practices - `feature-dev:code-explorer` - Trace execution paths, map architecture, understand dependencies - `feature-dev:code-architect` - Design feature architectures based on existing patterns ### Refactoring Agents ```javascript // Architecture analysis and planning Task({ subagent_type: "refactor:architect", description: "Plan refactoring", prompt: "Analyze code architecture and create a prioritized optimization plan" }) // Implementation Task({ subagent_type: "refactor:refactor-code", description: "Implement refactoring", prompt: "Implement the architectural optimizations while preserving functionality" }) // Test coverage Task({ subagent_type: "refactor:refactor-test", description: "Refactoring test coverage", prompt: "Analyze coverage, add missing tests, ensure all tests pass" }) // Code simplification (post-refactor cleanup) Task({ subagent_type: "refactor:simplifier", description: "Simplify refactored code", prompt: "Simplify and refine recently changed code for clarity and consistency" }) // Security regression check Task({ subagent_type: "refactor:security-review", description: "Security review of refactored code", prompt: "Review refactored code for security regressions and vulnerabilities" }) ``` ### CI/CD and Infrastructure Agents ```javascript // CI pipeline design Task({ subagent_type: "sdlc:ci-architect", description: "Design CI pipeline", prompt: "Configure GitHub Actions workflow for this project" }) ``` ### Bug Reproduction and Testing ```javascript // Bug reproduction (full tool access) Task({ subagent_type: "general-purpose", description: "Validate bug", prompt: "Reproduce and validate this reported bug: [description]" }) // Test generation Task({ subagent_type: "auto-harness:test-generator", description: "Generate tests", prompt: "Generate comprehensive test definitions for this component" }) ``` ### RLM Agents Content-aware chunk analyzers — the Team Lead selects the analyst based on detected content type. **Single-file mode:** One analyst type per session (determined by content type). **Multi-file mode:** Different analyst types run simultaneously when a directory contains mixed content types. 1 analyst per task (fresh context each), distributed proportionally across content types, staged spawning in batches of ~15 for large workloads. See [Multi-File Directory Analysis](../rlm-pattern/SKILL.md#multi-file-directory-analysis). **IMPORTANT:** In actual RLM workflows, spawn these as **teammates** (with `team_name` + `name`) so they communicate via `SendMessage` instead of dumping results into the leader's context. In multi-file mode, analysts write findings to task descriptions via `TaskUpdate` and send only one-line summaries to team-lead. See [RLM Pattern](../rlm-pattern/SKILL.md) for the full team lifecycle. The examples below show the `subagent_type` syntax only: ```javascript // Source code analysis (code-aware boundaries) Task({ subagent_type: "swarm:rlm-code-analyzer", description: "Analyze code chunk", prompt: "Query: Review for security issues\nFile: /tmp/rlm-chunks/chunk-01.py\nLanguage: python\nAnalysis focus: security\nThis is chunk 1 of 10." }) // CSV data analysis (header-preserving chunks) Task({ subagent_type: "swarm:rlm-data-analyzer", description: "Analyze data chunk", prompt: "Query: Analyze distribution by region\nFile: /tmp/rlm-chunks/chunk-03.csv\nThis is chunk 3 of 9.\nKey columns: region, plan, mrr" }) // JSON analysis (schema-aware chunks) Task({ subagent_type: "swarm:rlm-json-analyzer", description: "Analyze JSON chunk", prompt: "Query: Report schema patterns and anomalies\nFile: /tmp/rlm-chunks/chunk-02.jsonl\nFormat: jsonl\nThis is chunk 2 of 8." }) // General chunk analysis (logs, prose, config, other) Task({ subagent_type: "swarm:rlm-chunk-analyzer", description: "Analyze log chunk", prompt: "Query: What errors occurred?\nFile: /var/log/app/server.log\nStart line: 1\nEnd line: 200\nThis is chunk 1 of 10." }) // Synthesis (higher quality) Task({ subagent_type: "swarm:rlm-synthesizer", description: "Synthesize findings", prompt: "Original query: What errors occurred?\n\nFindings:\n[...findings JSON...]" }) ``` **RLM agents (defined by this plugin):** - `swarm:rlm-code-analyzer` — Haiku model, code-aware chunk analysis with scope context and analysis focus - `swarm:rlm-data-analyzer` — Haiku model, CSV/TSV chunk analysis with column distributions and statistics - `swarm:rlm-json-analyzer` — Haiku model, JSON/JSONL chunk analysis with schema patterns and field distributions. Also used by the [JSONL Log Analyzer](../jsonl-log-analyzer/SKILL.md) skill for log-specific schema-aware analysis - `swarm:rlm-chunk-analyzer` — Haiku model, general-purpose chunk analysis for logs, prose, config, markup - `swarm:rlm-synthesizer` — Sonnet model, aggregates findings from multiple chunk analyses into coherent reports **Do NOT override analyst models.** Do not pass `model: "sonnet"` or `model: "opus"` in the Task tool call when spawning analyst agents. The agent frontmatter defines `model: haiku` because structured counting, frequency analysis, and JSON output are well within Haiku's capability. Overriding to a more expensive model burns 10-50x the cost per chunk with no material quality gain. Only the synthesizer uses Sonnet. Leave the `model` parameter unset — let the agent definition's default apply. --- ## Agent Type Naming Convention Plugin agents use the format: `{plugin}:{agent-name}` or `{plugin}:{category}:{agent-name}` Examples: - `sdlc:security-reviewer` - `feature-dev:code-reviewer` - `refactor:architect` - `code-simplifier:code-simplifier` Built-in agents use simple names: `Bash`, `Explore`, `Plan`, `general-purpose`, `claude-code-guide`, `statusline-setup`. Swarm plugin agents follow the same convention: - `swarm:rlm-code-analyzer` - `swarm:rlm-data-analyzer` - `swarm:rlm-json-analyzer` - `swarm:rlm-chunk-analyzer` - `swarm:rlm-synthesizer` --- > Converted and distributed by [TomeVault](https://tomevault.io/claim/zircote) — claim your Tome and manage your conversions.