mcpField
A
agent-builder

agent-builder

github.com/mathews-tomAgent workflows340113 installsUpdated today
Repository

About agent-builder

agent-builder is a skill for building agents and automations with Claude Code's headless CLI and Python Agent SDK. It provides implementation guidance, CLI references, and security practices while steering away from the raw Anthropic API.

Key features

  1. 01Python Agent SDK guidance
  2. 02Headless CLI command guidance
  3. 03CLI commands and options reference
  4. 04Custom tools and hooks guidance
  5. 05Security and testing checklists

Use cases

  1. 01Create a Python agent with custom tools
  2. 02Run Claude Code queries from scripts or CI/CD
  3. 03Add hooks to control agent execution

MCP support

Covers creating SDK MCP servers with custom tools and using MCP settings inherited from Claude Code. The documented server patterns use stdio transport.

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/mathews-tom/armory --skill agent-builder

After installing, type/agent-builderin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

evals/
cases.yaml
references/
api-vs-sdk.md
best-practices.md
cli-reference.md
example-agent.md
headless-cli.md
output-format.md
sdk-python.md
use-cases.md

Details

From the project README

Agent Builder - Claude SDK & CLI Expert

Triggers:

  • "build agent", "create agent", "agent sdk", "claude sdk"
  • "headless mode", "programmatic", "cli command"
  • "claude -p", "query programmatically"
  • "custom tools", "mcp server", "sdk mcp"
  • "claude code api", "agent options"

Prefer Claude Code Headless Mode

This skill covers Claude Code's headless mode and the Agent SDK — not the raw Anthropic API.

Preferred: Claude Code CLI headless mode (claude -p)
Preferred: Claude Agent SDK (wraps Claude Code CLI)
Avoid:     Raw Anthropic API (anthropic.Anthropic())
Avoid:     Direct API calls with API keys

Why this matters:

  • The Agent SDK wraps the Claude Code CLI — it does not use the raw Anthropic API
  • Authentication comes from existing ~/.claude/ config — no API keys needed
  • All settings, MCP servers, and configuration inherit from your Claude Code setup
  • You get Claude Code's full agent loop, tools, and context management

Rule: If code uses anthropic.Anthropic(), anthropic.messages.create(), or requires ANTHROPIC_API_KEY, that is the wrong approach. Use claude -p or claude_agent_sdk instead.


Core Capabilities

  1. Claude Agent SDK Python - Programmatic agent creation with custom tools and hooks (wraps Claude Code CLI)
  2. Headless/Print Mode - Run Claude Code from CLI, scripts, CI/CD (claude -p)
  3. CLI Reference - All commands, flags, and configuration options

All use Claude Code's existing authentication from ~/.claude/ — no API keys required.


Documentation Sources


Workflow

  1. Understand the requirement - What type of agent/automation is needed?
  2. Check dependencies - Verify Python version, packages, Claude Code installation
  3. Reference live docs - Fetch relevant documentation if details are unclear
  4. Build confidently - Write production-ready code with proper error handling
  5. Test immediately - Run and validate the implementation

Reference Files

Load only the reference file relevant to the current task.

TaskLoad
Distinguishing raw Anthropic API from Claude Code SDK patternsreferences/api-vs-sdk.md
Writing a Python agent with the Agent SDK (install, query, client, tools, hooks, errors)references/sdk-python.md
Using headless claude -p mode (basic, JSON schema, streaming, tool approval, sessions, system prompts)references/headless-cli.md
CLI commands, flags table, dynamic subagents, permission rule syntaxreferences/cli-reference.md
Use-case templates: CI/CD pipeline, code review, custom analysis tool, database query agentreferences/use-cases.md
Agent SDK and CLI/Headless best practicesreferences/best-practices.md
Complete end-to-end agent example (tools + hooks + client)references/example-agent.md
Output format conventions for produced artifactsreferences/output-format.md

Security

  • Do not use --dangerously-skip-permissions in production
  • Validate inputs in custom tools
  • Use permission rules to block destructive commands
  • Set budget limits with --max-budget-usd
  • Implement hooks for sensitive operations
  • Review allowed tools before automation

Quick Decision Tree

Need to...

  • Run one-off query → claude -p "query"
  • Build custom agent → Agent SDK with ClaudeSDKClient
  • Add custom tools → SDK MCP server with @tool decorator
  • Control execution → Hooks with HookMatcher
  • Stream responses → --output-format stream-json
  • Get structured data → --json-schema
  • Continue conversation → --continue or --resume
  • Run in CI/CD → claude -p with --allowedTools
  • Integrate with app → Python SDK with query() or ClaudeSDKClient

When to Fetch Docs

Fetch live documentation when:

  • API signatures or parameters are unclear
  • New features or flags are mentioned
  • Error messages reference unknown configuration
  • Implementing complex hooks or MCP servers
  • User asks about specific capabilities

Use WebFetch tool to pull latest documentation from source URLs.


Implementation Checklist

Before writing code:

  • Verify: Using Claude Code headless mode (claude -p or claude_agent_sdk) — not raw Anthropic API
  • Verify: No API keys in code — authentication comes from ~/.claude/ config
  • Confirm Python version (3.10+)
  • Verify Claude Code CLI installation (which claude)
  • Check required packages with uv pip list
  • Understand the specific use case
  • Determine if SDK or CLI approach is needed

After writing code:

  • Verify: Code uses claude_agent_sdk or claude -p — not anthropic.Anthropic()
  • Verify: No ANTHROPIC_API_KEY or api_key= parameters in code
  • Add error handling for all SDK exceptions
  • Test with actual Claude Code installation
  • Validate tool permissions and security
  • Set appropriate limits (turns, budget)
  • Document custom tools and their purposes

Skill Invocation

This skill provides:

  • Complete Agent SDK implementation guidance
  • Headless/CLI command construction
  • Custom tool creation with MCP servers
  • Hook implementation for control flow
  • Security best practices
  • Live documentation fetching when needed

Ask specific questions about building agents, running headless commands, or CLI usage.


Limitations

  • The Agent SDK is Python-only (Python 3.10+); no JavaScript or other language bindings are covered here.
  • Requires Claude Code CLI installed and authenticated via ~/.claude/ before any SDK or headless usage works.
  • This skill does not cover raw Anthropic API usage (anthropic.Anthropic()); see the Anthropic API docs for that.
  • Agent processes launched via the SDK are ephemeral by default; session persistence requires explicit --resume or session ID capture.
  • MCP server patterns in this skill use stdio transport; HTTP-based MCP transports require separate configuration not covered here.

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