Agent skill

Autonomous Agent Harness

by affaan-m in affaan-m/ECC

Transform Claude Code into a fully autonomous agent system with persistent memory, scheduled operations, computer use, and task queuing.

MITAuto-check passedAgent Workflows

Install Autonomous Agent Harness

skills CLI
$ npx skills add affaan-m/ECC --skill autonomous-agent-harness -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install affaan-m/ECC autonomous-agent-harness --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/affaan-m/ECC.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/autonomous-agent-harness .claude/skills/autonomous-agent-harness && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
autonomous-agent-harness
GitHub stars
277k
Used in
2 other repos
Token cost
~2.9k tokens
SKILL.md length
901 words
Files
1
Skills in repo
683
Repo updated
First seen
Licence
MIT

At a glance

Transform Claude Code into a fully autonomous agent system with persistent memory, scheduled operations, computer use, and task queuing.

  • Works in 9 steps: Persistent Memory → Scheduled Operations (Crons) → Dispatch / Remote Agents → …
  • The user wants continuous autonomous operation
  • SKILL.md covers Consent and Safety Boundaries, When to Activate, Architecture and Core Components, plus 4 more sections
  • Calls claude and npx

What it does

Autonomous Agent Harness is an agent skill from affaan-m/ECC. 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.

Its SKILL.md is about 2.9k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Agent Workflows, covering Autonomous loops, Scheduled and recurring tasks and Desktop control. It works with Model Context Protocol. The repository describes itself as: The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond. The licence is MIT.

When your agent uses it

  • The user wants continuous autonomous operation
  • Scheduled tasks
  • A self-directing agent loop

Example prompts

  • “/autonomous-agent-harness”

Requirements

  • Node.js

Workflow steps

9 steps, taken from the step headings in SKILL.md.

  1. Persistent Memory
  2. Scheduled Operations (Crons)
  3. Dispatch / Remote Agents
  4. Computer Use
  5. Task Queue
  6. Configure MCP Servers
  7. Create Base Crons
  8. Initialize Memory Graph
  9. Enable Computer Use (Optional)

What it can do on your machine

Read from SKILL.md and the folder at commit 2d515e4. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • claude
    • npx

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • code.claude.com
    • platform.claude.com
    • github.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Autonomous Agent Harness loads about 2.9k tokens when it runs. Until then it costs about 99 tokens; SKILL.md has 901 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~99
When it runs · the whole SKILL.md, loaded when a task matches
~2.9k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from affaan-m/ECC at commit 2d515e4, republished under its MIT licence (© affaan-m). 901 words, ~2,942 tokens.

Download SKILL.mdSave it as .claude/skills/autonomous-agent-harness/SKILL.md (or your agent's skills folder).
name
autonomous-agent-harness
description
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.
metadata.origin
ECC

Autonomous Agent Harness

Combine Claude Code's session tools with separately configured scheduling, memory, and computer-use integrations. This is a setup pattern, not a bundled always-on runtime.

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 entities
2. Scheduled Operations (Crons)

Use Claude Code's native scheduled tasks for recurring prompts within an interactive session. These tasks are session-scoped; an external scheduler is required for work that must run independently of an open session. No scheduling MCP server is required for /loop.

Setting up a cron:

# In an interactive Claude Code session
/loop 30m Review open PRs in this repository and summarize CI failures.

For a one-shot run from a shell, set the working directory before invoking the CLI:

bash
cd "/path/to/repo" && claude -p "Review open PRs and summarize"

Use an OS scheduler or CI schedule to invoke that command repeatedly when no interactive session is running. Configure the runner's authentication and tool permissions separately.

Useful cron patterns:

PatternScheduleUse Case
Daily standup0 9 * * 1-5Review PRs, issues, deploy status
Weekly review0 10 * * 1Code quality metrics, test coverage
Hourly monitor0 * * * *Production health, error rate checks
Nightly build0 2 * * *Run full test suite, security scan
Pre-meeting*/30 * * * *Prepare context for upcoming meetings
3. Dispatch / Remote Agents

Have an authenticated CI job or webhook receiver invoke Claude Code in a workspace it owns. The supported entrypoint is programmatic CLI mode, not a public Anthropic dispatch endpoint.

Dispatch patterns:

bash
# Run inside the CI workspace
cd "/path/to/repo" && claude -p "Build failed on main. Diagnose the failure."

# Trigger from webhook
# GitHub webhook -> authenticated CI runner -> claude -p -> reviewable result

# Trigger from another agent
claude -p "Analyze the output of the security scan and create issues for findings"
4. Computer Use

Computer control needs a separately configured integration. Anthropic's computer-use tool and reference environment require an application to execute tool calls in an isolated desktop environment. Adding an MCP package name does not supply that environment.

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 issues

Replacing Hermes

Hermes ComponentECC EquivalentHow
Gateway/RouterCLI + external schedulerAn authenticated runner starts agent sessions
Memory SystemClaude memory + MCP memory serverBuilt-in persistence + knowledge graph
Tool RegistryMCP serversDynamically loaded tool providers
OrchestrationECC skills + agentsSkill definitions direct agent behavior
Computer UseSeparately configured integrationBrowser or desktop control in an isolated environment
Context ManagerSession management + memoryECC 2.0 session lifecycle
Task QueueMemory-persisted task listTodoWrite + memory files
Show full SKILL.md (335 more words)Show less

Setup Guide

Step 1: Configure MCP Servers

Memory MCP is optional. The MCP reference memory server is published as @modelcontextprotocol/server-memory; version 2026.8.31 was verified on the public npm registry on 2026-09-07. It is a reference implementation, not an ECC-bundled service.

After reviewing that package and approving its use, merge this entry into the user-scoped MCP configuration in ~/.claude.json, preserving existing settings. Replace MEMORY_FILE_PATH with an absolute path in a private directory you own. See Claude Code MCP configuration for CLI registration and Windows cmd /c npx configuration.

json
{
  "mcpServers": {
    "memory": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-memory@2026.8.31"],
      "env": {
        "MEMORY_FILE_PATH": "/absolute/path/to/private/memory.jsonl"
      }
    }
  }
}

Do not register guessed or unpublished npm packages: npx -y would execute whatever is later published under that name. Verify the exact package, publisher, and version before adding another server. Scheduling and computer use do not require the three unpublished package names previously listed here.

Step 2: Create Base Crons

For polling during an interactive session, enter:

text
/loop 30m Review open PRs in this repository and summarize CI failures.

For daily or weekly work that must survive a closed session, configure an external scheduler, such as an OS cron job or GitHub Actions, to run the one-shot command from Step 2 of Core Components. Calling claude -p to request a schedule does not provision an always-on scheduler. Choose the schedule, workspace, and allowed actions explicitly before enabling it.

Step 3: Initialize Memory Graph
bash
# 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)

Follow the computer-use reference environment linked above, or the documentation for a specific browser integration you have reviewed. Grant only the required permissions and verify a harmless action in the isolated environment before adding it to scheduled workflows.

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 status
Personal 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 review
Meeting 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 memory

Constraints

  • Native scheduled prompts share their interactive session. External scheduler invocations start separate sessions unless explicitly resumed.
  • Computer use requires explicit permission grants. Don't assume access.
  • CLI automation still consumes model usage and is subject to the configured provider's limits. Choose appropriate scheduler 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.

© affaan-m, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/autonomous-agent-harness of affaan-m/ECC.

Open the folder on GitHubat commit 2d515e4

Used in 2 other repositories

We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 2 other GitHub owners. This page covers the copy in affaan-m/ECC, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Autonomous Agent Harness next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Autonomous Agent Harness compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Autonomous Agent Harness this skillaffaan-m/ECC277k2 repos~2.9kAutomated safety check: PassMIT
Cherry Studio Tool GuideCherryHQ/cherry-studio53k—~1.9kAutomated safety check: PassAGPL-3.0
Toolifycoreyhaines31/makerskills851—~2.9kAutomated safety check: NotesMIT
agtx One-Shot Project Runnerfynnfluegge/agtx1.7k—~3.8kAutomated safety check: PassApache-2.0
Harness 24hthu-nmrc/OpenHarness118—~3.6kAutomated safety check: PassApache-2.0
MetaBot CLIxvirobotics/metabot994—~573Automated safety check: PassMIT

Similar skills

  • Cherry Studio Tool Guide

    CherryHQ/cherry-studio

    Routes an agent inside Cherry Studio to the right first-party tool or bundled runtime for local scripts, documents, memory, schedules, knowledge bases, MCP servers and more.

    53k GitHub stars~1.9k tokensUpdated today
    Agent WorkflowsAuto-check passed
  • Toolify

    coreyhaines31/makerskills

    When you want to integrate an external tool, API, MCP server, or service into a project — the wizard walks you through auth, config, env vars, client wrapper code, example usage, and an optional…

    851 GitHub stars~2.9k tokensUpdated 2 days ago
    Agent WorkflowsAuto-check: notes
  • Runs a whole project unattended on an agtx kanban board, decomposing the goal, starting tasks, unblocking workers and merging each result.

    1.7k GitHub stars~3.8k tokensUpdated 9 days ago
    Agent WorkflowsAuto-check passed
  • Harness 24h

    thu-nmrc/OpenHarness

    A production-grade framework for long-running, autonomous agents based on Harness Engineering principles.

    118 GitHub stars~3.6k tokensUpdated 6 mo ago
    Agent WorkflowsAuto-check passed
  • MetaBot CLI

    xvirobotics/metabot

    Documents the unified `metabot` CLI for personal memory, the skill hub, durable agent messaging, the agent registry, T5T status and scheduling.

    994 GitHub stars~573 tokensUpdated 25 days ago
    Agent WorkflowsAuto-check passed
  • Claude Session Search

    tombelieber/claude-view

    Search your Claude Code session history through the claude-view MCP server, matching summaries, commit messages and project or branch names, and present the most relevant sessions.

    111 GitHub stars~3k tokensUpdated 10 days ago
    Agent WorkflowsAuto-check passed

More from affaan-m/ECC

All 682 skills in this repo
  • Skill Stocktake

    affaan-m/ECC

    Audits your installed Claude skills and commands for quality, with a quick mode for recently changed skills and a full mode that evaluates all of them through subagents.

    277k GitHub starsUsed in 5 repos~3.1k tokens
    Auto-check passed
  • Ingests, indexes, searches, edits and monitors video, audio and live streams through the VideoDB Python SDK, returning stream links, clips and timestamps.

    277k GitHub starsUsed in 3 repos~3.5k tokens
    Auto-check: notes
  • Docs Governance

    affaan-m/ECC

    Route broad documentation-governance requests to existing ECC skills and run an opt-in, read-only audit of mapped documentation roles, links, ADR indexes, and evidence references.

    277k GitHub stars~1.1k tokensUpdated today
    Auto-check passed
  • Rules Distillation

    affaan-m/ECC

    Scans installed skills for principles that recur across them and proposes rule-file changes: append, revise, add a section, create a file or leave as covered.

    277k GitHub starsUsed in 2 repos~2.3k tokens
    Auto-check passed
  • Builds DRAFT counterparty agreements from one markdown template and a small JSON spec per party, with clauses picked by the party's role.

    277k GitHub stars~2.9k tokensUpdated today
    Auto-check passed
  • Set an ECC-specific frontend design direction for production UI work.

    277k GitHub starsUsed in 1 repo~2.2k tokens
    Auto-check passed

Questions about Autonomous Agent Harness

What does Autonomous Agent Harness do?

Transform Claude Code into a fully autonomous agent system with persistent memory, scheduled operations, computer use, and task queuing. Autonomous Agent Harness is an agent skill from affaan-m/ECC. Transform Claude Code into a fully autonomous agent system with persistent memory, scheduled operations, computer use, and task queuing.

When should I use Autonomous Agent Harness?

Autonomous Agent Harness fits situations like: the user wants continuous autonomous operation; scheduled tasks; A self-directing agent loop.

How do I install Autonomous Agent Harness in Claude Code?

Run `npx skills add affaan-m/ECC --skill autonomous-agent-harness -a claude-code`. Or copy the skill folder (skills/autonomous-agent-harness in affaan-m/ECC) into .claude/skills/autonomous-agent-harness in your project. Claude Code loads it when a task matches its description.

How do I install Autonomous Agent Harness in Codex?

Run `npx skills add affaan-m/ECC --skill autonomous-agent-harness -a codex`. Or copy the skill folder (skills/autonomous-agent-harness in affaan-m/ECC) into .agents/skills/autonomous-agent-harness in your project. Codex loads it when a task matches its description.

Can I use Autonomous Agent Harness in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add affaan-m/ECC --skill autonomous-agent-harness -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/autonomous-agent-harness, .gemini/skills/autonomous-agent-harness, .github/skills/autonomous-agent-harness and .opencode/skills/autonomous-agent-harness in your project.

What does Autonomous Agent Harness need to run?

Going by SKILL.md and its folder, Autonomous Agent Harness needs the command-line tools its instructions call (claude and npx). Our summary lists: Node.js.

Does Autonomous Agent Harness access the network?

SKILL.md names 3 domains. As links in the text: code.claude.com, platform.claude.com and github.com. This is read from the text; nothing was executed.

Is Autonomous Agent Harness safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Autonomous Agent Harness use?

Autonomous Agent Harness is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Autonomous Agent Harness use?

About 2.9k tokens (SKILL.md is roughly 12k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Autonomous Agent Harness?

Skills that share tags, products or a category with Autonomous Agent Harness: Cherry Studio Tool Guide (CherryHQ/cherry-studio, 53k stars), Toolify (coreyhaines31/makerskills, 851 stars), agtx One-Shot Project Runner (fynnfluegge/agtx, 1.7k stars) and Harness 24h (thu-nmrc/OpenHarness, 118 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Autonomous Agent Harness?

affaan-m (a GitHub user) maintains it in affaan-m/ECC, which has 276,673 GitHub stars. The repository holds 683 skills in this directory. The repository was last updated on October 11, 2026.

Source: affaan-m/ECC on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.