autonomous-agent-harness
Skill1 starsChanged 3 months agoMITView on GitHub
Transform Claude Code into a fully autonomous agent system with persistent memory, scheduled operations, computer use, and task queuing. Replaces standalone agent frameworks (Hermes, AutoGPT) by leveraging Claude Code's native crons, dispatch, MCP tools, and memory. Use when the user wants continuous autonomous operation, scheduled tasks, or a self-directing agent loop.
- Reads credentials
- Sends data out
We split this skill into the rules it gives an agent
5 rules. 4 are common, 0 are distinctive, and 1 is very specific to this project.
4
Common
Most of the 7 edited versions we read keep these.
0
Distinctive
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Common: line 15
Prefer dry-run plans and local queue files before enabling recurring or event-driven actions.
- Common: line 58
Use Claude Code's built-in memory system enhanced with MCP memory server for structured data.
- Common: line 87
Use Claude Code's scheduled tasks to create recurring agent operations.
- Very specific: line 190
Ensure these are in ~/.claude.json:
- Common: line 273
Always verify that scheduled tasks completed successfully.
“Common” is measured: kept by at least 6 in 10 of the 7 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Autonomous Agent Harness
Turn Claude Code into a persistent, self-directing agent system using only native features and MCP servers.
Consent and Safety Boundaries
Autonomous operation must be explicitly requested and scoped by the user. Do not create schedules, dispatch remote agents, write persistent memory, use computer control, post externally, modify third-party resources, or act on private communications unless the user has approved that capability and the target workspace for the current setup.
Prefer dry-run plans and local queue files before enabling recurring or event-driven actions. Keep credentials, private workspace exports, personal datasets, and account-specific automations out of reusable ECC artifacts.
When to Activate
- User wants an agent that runs continuously or on a schedule
- Setting up automated workflows that trigger periodically
- Building a personal AI assistant that remembers context across sessions
- User says "run this every day", "check on this regularly", "keep monitoring"
- Wants to replicate functionality from Hermes, AutoGPT, or similar autonomous agent frameworks
- Needs computer use combined with scheduled execution
Architecture
┌──────────────────────────────────────────────────────────────┐
│ Claude Code Runtime │
│ │
│ ┌──────────┐ ┌──────────┐ ┌──────────┐ ┌─────────────┐ │
│ │ Crons │ │ Dispatch │ │ Memory │ │ Computer │ │
│ │ Schedule │ │ Remote │ │ Store │ │ Use │ │
│ │ Tasks │ │ Agents │ │ │ │ │ │
│ └────┬─────┘ └────┬─────┘ └────┬─────┘ └──────┬──────┘ │
│ │ │ │ │ │
│ ▼ ▼ ▼ ▼ │
│ ┌──────────────────────────────────────────────────────┐ │
│ │ ECC Skill + Agent Layer │ │
│ │ │ │
│ │ skills/ agents/ commands/ hooks/ │ │
│ └──────────────────────────────────────────────────────┘ │
│ │ │ │ │ │
│ ▼ ▼ ▼ ▼ │
│ ┌──────────────────────────────────────────────────────┐ │
│ │ MCP Server Layer │ │
│ │ │ │
│ │ memory github exa supabase browser-use │ │
│ └──────────────────────────────────────────────────────┘ │
└──────────────────────────────────────────────────────────────┘Core Components
1. Persistent Memory
Use Claude Code's built-in memory system enhanced with MCP memory server for structured data.
Built-in memory (~/.claude/projects/*/memory/):
- User preferences, feedback, project context
- Stored as markdown files with frontmatter
- Automatically loaded at session start
MCP memory server (structured knowledge graph):
- Entities, relations, observations
- Queryable graph structure
- Cross-session persistence
Memory patterns:
# Short-term: current session context
Use TodoWrite for in-session task tracking
# Medium-term: project memory files
Write to ~/.claude/projects/*/memory/ for cross-session recall
# Long-term: MCP knowledge graph
Use mcp__memory__create_entities for permanent structured data
Use mcp__memory__create_relations for relationship mapping
Use mcp__memory__add_observations for new facts about known entities2. Scheduled Operations (Crons)
Use Claude Code's scheduled tasks to create recurring agent operations.
Setting up a cron:
# Via MCP tool
mcp__scheduled-tasks__create_scheduled_task({
name: "daily-pr-review",
schedule: "0 9 * * 1-5", # 9 AM weekdays
prompt: "Review all open PRs in affaan-m/everything-claude-code. For each: check CI status, review changes, flag issues. Post summary to memory.",
project_dir: "/path/to/repo"
})
# Via claude -p (programmatic mode)
echo "Review open PRs and summarize" | claude -p --project /path/to/repoUseful cron patterns:
| Pattern | Schedule | Use Case |
| Daily standup | 0 9 * * 1-5 | Review PRs, issues, deploy status |
| Weekly review | 0 10 * * 1 | Code quality metrics, test coverage |
| Hourly monitor | 0 * * * * | Production health, error rate checks |
| Nightly build | 0 2 * * * | Run full test suite, security scan |
| Pre-meeting | */30 * * * * | Prepare context for upcoming meetings |
3. Dispatch / Remote Agents
Trigger Claude Code agents remotely for event-driven workflows.
Dispatch patterns:
# Trigger from CI/CD
curl -X POST "https://api.anthropic.com/dispatch" \
-H "Authorization: Bearer $ANTHROPIC_API_KEY" \
-d '{"prompt": "Build failed on main. Diagnose and fix.", "project": "/repo"}'
# Trigger from webhook
# GitHub webhook → dispatch → Claude agent → fix → PR
# Trigger from another agent
claude -p "Analyze the output of the security scan and create issues for findings"4. Computer Use
Leverage Claude's computer-use MCP for physical world interaction.
Capabilities:
- Browser automation (navigate, click, fill forms, screenshot)
- Desktop control (open apps, type, mouse control)
- File system operations beyond CLI
Use cases within the harness:
- Automated testing of web UIs
- Form filling and data entry
- Screenshot-based monitoring
- Multi-app workflows
5. Task Queue
Manage a persistent queue of tasks that survive session boundaries.
Implementation:
# Task persistence via memory
Write task queue to ~/.claude/projects/*/memory/task-queue.md
# Task format
---
name: task-queue
type: project
description: Persistent task queue for autonomous operation
---
## Active Tasks
- [ ] PR #123: Review and approve if CI green
- [ ] Monitor deploy: check /health every 30 min for 2 hours
- [ ] Research: Find 5 leads in AI tooling space
## Completed
- [x] Daily standup: reviewed 3 PRs, 2 issuesReplacing Hermes
| Hermes Component | ECC Equivalent | How |
| Gateway/Router | Claude Code dispatch + crons | Scheduled tasks trigger agent sessions |
| Memory System | Claude memory + MCP memory server | Built-in persistence + knowledge graph |
| Tool Registry | MCP servers | Dynamically loaded tool providers |
| Orchestration | ECC skills + agents | Skill definitions direct agent behavior |
| Computer Use | computer-use MCP | Native browser and desktop control |
| Context Manager | Session management + memory | ECC 2.0 session lifecycle |
| Task Queue | Memory-persisted task list | TodoWrite + memory files |
Setup Guide
Step 1: Configure MCP Servers
Ensure these are in ~/.claude.json:
{
"mcpServers": {
"memory": {
"command": "npx",
"args": ["-y", "@anthropic/memory-mcp-server"]
},
"scheduled-tasks": {
"command": "npx",
"args": ["-y", "@anthropic/scheduled-tasks-mcp-server"]
},
"computer-use": {
"command": "npx",
"args": ["-y", "@anthropic/computer-use-mcp-server"]
}
}
}Step 2: Create Base Crons
# Daily morning briefing
claude -p "Create a scheduled task: every weekday at 9am, review my GitHub notifications, open PRs, and calendar. Write a morning briefing to memory."
# Continuous learning
claude -p "Create a scheduled task: every Sunday at 8pm, extract patterns from this week's sessions and update the learned skills."Step 3: Initialize Memory Graph
# Bootstrap your identity and context
claude -p "Create memory entities for: me (user profile), my projects, my key contacts. Add observations about current priorities."Step 4: Enable Computer Use (Optional)
Grant computer-use MCP the necessary permissions for browser and desktop control.
Example Workflows
Autonomous PR Reviewer
Cron: every 30 min during work hours
1. Check for new PRs on watched repos
2. For each new PR:
- Pull branch locally
- Run tests
- Review changes with code-reviewer agent
- Post review comments via GitHub MCP
3. Update memory with review statusPersonal Research Agent
Cron: daily at 6 AM
1. Check saved search queries in memory
2. Run Exa searches for each query
3. Summarize new findings
4. Compare against yesterday's results
5. Write digest to memory
6. Flag high-priority items for morning reviewMeeting Prep Agent
Trigger: 30 min before each calendar event
1. Read calendar event details
2. Search memory for context on attendees
3. Pull recent email/Slack threads with attendees
4. Prepare talking points and agenda suggestions
5. Write prep doc to memoryConstraints
- Cron tasks run in isolated sessions — they don't share context with interactive sessions unless through memory.
- Computer use requires explicit permission grants. Don't assume access.
- Remote dispatch may have rate limits. Design crons with appropriate intervals.
- Memory files should be kept concise. Archive old data rather than letting files grow unbounded.
- Always verify that scheduled tasks completed successfully. Add error handling to cron prompts.
Other versions9 projects use a version of this.
Word for word · 1
- davidanthonyn/claude-skills★ 0100% same
Edited · 7
- Fmarzochi/EGC★ 6181% same
- gongyijie85/dsh-ecc★ 8100% same
- NISTALTALSON/essential-claude-skills★ 156% same
- Ronnasayd/aipp★ 155% same
- TironFox/everything-claude-code★ 1100% same
- pankaj-mahaur/Agent-Daemon★ 099% same
- renepf/claude-skills★ 0100% same
Wrote their own version · 1
- thanvish21/hcc-bundle★ 0same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
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