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housegarofalo/claude-code-base4 installs

autonomous-agent-harness

Set up autonomous coding agent projects with long-running harnesses using Archon MCP for state management. Creates complete project scaffolds with initializer/coding agent prompts, feature tracking, session handoffs, security configuration, and browser testing integration. Based on Anthropic's effective harnesses guide. Use when building autonomous coding agents, long-running AI workflows, or multi-session development projects.

How do I install this agent skill?

npx skills add https://github.com/housegarofalo/claude-code-base --skill autonomous-agent-harness
view source ↗

Is this agent skill safe to install?

  • Gen Agent Trust Hubpass

    The skill provides a framework for generating autonomous coding agent harnesses with persistent state management via the Archon MCP server. It incorporates significant security controls, including a restricted command permission model that denies high-risk operations like sudo and external network fetching. No malicious code, obfuscation, or data exfiltration vectors were detected during the analysis.

  • Socketwarn

    1 alert: gptAnomaly

  • Snykwarn

    Risk: MEDIUM · 1 issue

  • Runlayerfail

    1/1 file flagged

What does this agent skill do?

Autonomous Coding Agent Harness Setup

Create fully-configured autonomous coding agent projects that can work across multiple sessions with proper state management, handoffs, and testing. Uses Archon MCP for project/task tracking, enabling persistent state management and context preservation.

Triggers

Use this skill when:

  • Building autonomous coding agent projects
  • Setting up long-running AI workflows with state management
  • Creating multi-session development projects
  • Implementing agent harnesses with handoffs
  • Building coding agents that persist state across sessions
  • Keywords: autonomous agent, harness, coding agent, archon, state management, session handoff, multi-session

Quick Start

Use these prompts to interact with the harness system:

CommandDescription
/harness-setupLaunch full setup wizard
/harness-quickQuick setup with smart defaults
/harness-initInitialize project (first session)
/harness-nextStart next coding session
/harness-statusCheck project status
/harness-resumeResume existing project

Architecture Overview

                    MULTI-AGENT PIPELINE

   /harness-setup -> @harness-wizard
         |
         v
   /harness-init -> @harness-initializer
         |
         v
   /harness-next -> @harness-coder
         |
         +---> @harness-tester (parallel)
         |
         +---> @harness-reviewer (before completion)
         |
         v
   [Repeat for each feature]

   State Management: Archon MCP (Projects, Tasks, Documents)

Agent Pipeline

AgentRoleWhen Used
@harness-wizardInteractive setupInitial configuration
@harness-initializerGenerate tasks from specFirst session only
@harness-coderImplement featuresEvery coding session
@harness-testerRun tests & verifyAfter implementation (parallel)
@harness-reviewerCode reviewBefore marking complete

Features

  • Multi-Agent System: Four specialized agents working together
  • Archon State Management: Projects, tasks, and documents via MCP
  • Clean Handoffs: Session notes and context for seamless continuation
  • Parallel Testing: Testing agent can run in background
  • Code Review: Optional review before feature completion
  • Multiple Execution Modes: Terminal, background, or SDK

Project Setup Questionnaire

When the user requests to set up an autonomous coding agent project, gather the following information systematically:

Phase 1: Project Basics

PROJECT BASICS

1. Project Name:
   What should the project be called? (e.g., "saas-dashboard", "e-commerce-api")

2. Project Description:
   Brief description of what you're building (1-3 sentences)

3. Project Type:
   - Web Application (Frontend + Backend)
   - API/Backend Only
   - CLI Application
   - Full-Stack with Database
   - Mobile App Backend
   - Other

4. GitHub Repository:
   Will this use a GitHub repo? If yes, provide URL (or "create new")

Phase 2: Technical Stack

TECHNICAL STACK

5. Primary Language:
   TypeScript/JavaScript, Python, Go, Rust, Java, Other

6. Framework (if applicable):
   - Frontend: (React, Vue, Svelte, Next.js, etc.)
   - Backend: (Express, FastAPI, Gin, Actix, Spring, etc.)

7. Database:
   PostgreSQL, MySQL/MariaDB, MongoDB, SQLite, Supabase, Firebase, None/TBD

8. Package Manager:
   npm, yarn, pnpm, pip/poetry, go mod, cargo

Phase 3: Agent Configuration

AGENT CONFIGURATION

9. Max Features/Tasks:
   How many features should the initializer create? (recommended: 20-50)
   Default: 30

10. Session Iteration Limit:
    Max iterations per coding session? (0 = unlimited)
    Default: 50

11. Claude Model:
    - claude-opus-4-5-20251101 (Recommended for complex projects)
    - claude-sonnet-4-20250514 (Faster, good balance)
    - claude-haiku-3-5-20241022 (Quick iterations)

12. MCP Servers to Enable:
    - Archon (Required - state management)
    - Playwright (Browser automation testing)
    - GitHub (Repository operations)
    - Brave Search (Web research)

Project Generation Workflow

After collecting all questionnaire responses, execute this workflow:

Step 1: Create Archon Project

# Create project in Archon
manage_project("create",
    title="<PROJECT_NAME>",
    description="<PROJECT_DESCRIPTION>",
    github_repo="<GITHUB_URL>"
)
# Save returned project_id for all subsequent operations

Step 2: Generate Directory Structure

<project_name>/
├── .archon_project.json        # Project marker with Archon project_id
├── .claude_settings.json       # Security settings and allowed commands
├── app_spec.txt                # Application specification
├── init.sh                     # Environment setup script
├── claude-progress.txt         # Session progress tracking
├── features.json               # Feature registry (pass/fail tracking)
├── prompts/
│   ├── initializer_prompt.md   # First session prompt
│   └── coding_prompt.md        # Continuation session prompt
├── src/                        # Application source code
├── tests/                      # Test files
└── docs/                       # Documentation

Step 3: Generate Configuration Files

.archon_project.json:

{
  "project_id": "<ARCHON_PROJECT_ID>",
  "project_name": "<PROJECT_NAME>",
  "created_at": "<TIMESTAMP>",
  "status": "initializing"
}

.claude_settings.json:

{
  "permissions": {
    "allow": [
      "Bash(npm:*)",
      "Bash(node:*)",
      "Bash(git:*)",
      "Bash(python:*)",
      "Bash(pip:*)",
      "Bash(pytest:*)",
      "Read", "Write", "Edit", "Glob", "Grep"
    ],
    "deny": [
      "Bash(rm -rf:*)",
      "Bash(sudo:*)",
      "Bash(curl:*)",
      "Bash(wget:*)"
    ]
  },
  "mcp_servers": ["archon", "playwright-mcp"],
  "model": "<SELECTED_MODEL>",
  "max_iterations": <ITERATION_LIMIT>
}

Handoff Workflow

Between Sessions

The coding agent should follow this handoff protocol:

  1. Update Progress File:

    ## Session: <DATE>
    
    ### Completed:
    - Task #1: Feature description (DONE)
    - Task #2: Feature description (IN PROGRESS)
    
    ### Blockers:
    - None / List any blockers
    
    ### Next Steps:
    - Continue Task #2
    - Start Task #3
    
    ### Notes for Next Session:
    - Important context or decisions made
    
  2. Update Archon META Task:

    manage_task("update",
        task_id="<META_TASK_ID>",
        description="Updated session summary:\n\n<PROGRESS_SUMMARY>"
    )
    
  3. Git Commit:

    git add .
    git commit -m "Session end: <SUMMARY>
    
    Completed: <TASK_LIST>
    Next: <NEXT_TASK>"
    

Archon MCP Quick Reference

Project Management

# Create project
manage_project("create", title="My App", description="...", github_repo="...")

# Get project
find_projects(project_id="uuid")

# List all projects
find_projects()

Task Management

# Create task
manage_task("create",
    project_id="...",
    title="Feature name",
    description="Details...",
    status="todo",
    assignee="Coding Agent",
    task_order=50,
    feature="Auth"
)

# Update task status
manage_task("update", task_id="...", status="doing")
manage_task("update", task_id="...", status="review")
manage_task("update", task_id="...", status="done")

# Get tasks
find_tasks(filter_by="project", filter_value="<project_id>")
find_tasks(filter_by="status", filter_value="todo")
find_tasks(task_id="<specific_task_id>")

Task Status Flow

todo -> doing -> review -> done

Best Practices

  1. Incremental Progress: Work on single features per session
  2. Test Everything: Verify E2E functionality, not just code changes
  3. Clean Handoffs: Leave environment ready for next session
  4. Explicit State: Never assume - always check Archon for current state
  5. Atomic Commits: Commit after each feature completion
  6. No Test Shortcuts: Never modify tests to pass artificially
  7. Document Decisions: Add context to Archon tasks and progress file
  8. Verify Before Claiming: Test features before marking complete

Troubleshooting

Common Issues

IssueSolution
Agent skips testingAdd explicit testing requirements in prompt
Lost context between sessionsCheck claude-progress.txt and Archon META task
Feature marked done but brokenRun E2E tests, update features.json status
Archon connection failedVerify MCP server configuration
Agent declares premature completionRequire explicit feature count verification

Recovery Commands

# Check project status
find_tasks(filter_by="project", filter_value="<PROJECT_ID>")

# View recent progress
cat claude-progress.txt
git log --oneline -10

# Verify features
cat features.json | jq '.features[] | select(.status=="failing")'

# Reset stuck task
manage_task("update", task_id="...", status="todo")

Notes

  • This skill requires Archon MCP server to be configured and running
  • Playwright MCP is recommended for E2E testing but optional
  • The agent harness works best with detailed, specific app specifications
  • For complex projects, consider breaking into phases (MVP, v1, v2)
  • Review and adjust generated prompts based on project-specific needs

Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.

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