agent-apprenticeship

Name: agent-apprenticeship
Author: Forsy-AI

Verified

The living ecosystem for AI agents learning from real-world work through iterative loops and training-signal exchange.

281stars

0forks

Added 6/20/2026

Installation

# Add to your Claude Code skills
git clone https://github.com/Forsy-AI/agent-apprenticeship

Getting Started

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Security ReportVerified

Last scanned: 6/20/2026

{
  "issues": [],
  "status": "PASSED",
  "scannedAt": "2026-06-20T07:50:15.126Z",
  "npmAuditRan": true,
  "pipAuditRan": true,
  "promptInjectionRan": true
}

README.md

Frequently Asked Questions

What is agent-apprenticeship?

agent-apprenticeship is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by Forsy-AI. The living ecosystem for AI agents learning from real-world work through iterative loops and training-signal exchange. It has 281 GitHub stars.

Is agent-apprenticeship safe to use?

Yes. agent-apprenticeship passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.

How do I install agent-apprenticeship?

Clone the repository with "git clone https://github.com/Forsy-AI/agent-apprenticeship" and add it to your Claude Code skills directory (see the Installation section above).

Are there alternatives to agent-apprenticeship?

Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh agent-apprenticeship against similar tools.

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Agent Apprenticeship

The living ecosystem where AI agents learn from real-world work through iterative workflow loops, reusable experience, and training signal exchange.

npx agent-apprenticeship init

As agents move into long-horizon, economically valuable work, Agent Apprenticeship creates the open infrastructure where real-world tasks generate reusable learning signals and challenging workflows advance through automated agent loops.

Agent Apprenticeship is designed for an infinite exchange of work experience between agents: useful work creates training signals, signals improve future work, and future work creates new signals for the ecosystem.

Agent Apprenticeship is built for loop iterations across domains, from simple tasks to complex specialized workflows. Apprentice agents can work with mentor agents to accomplish long-horizon, real-world tasks across model-assisted, expert-led, and hybrid modes, generating learning signals throughout the process.

The first seed dataset includes:

500+ curated seed tasks sourced and grounded from real world
495 reusable agent lessons
1000+ full agent execution traces
1000+ agent work episodes / task rollouts

The seed dataset spans specialized economically valuable tasks across domains and forms the first layer of the Agent Apprenticeship ecosystem.

Agent Apprenticeship is now available for anyone to start using with local agents including Codex, Cursor, Claude Code, OpenClaw, OpenCode, Hermes Agent, and custom agents, alongside different model providers. Users can run automated agent workflow loops locally, contribute agent learning signals back to the ecosystem, and use shared ecosystem signals to improve their own agents.

Agent Apprenticeship is also about the future of work and the economic value of agents. For every task executed through Agent Apprenticeship, the system can estimate task-level economic value, especially across specialized domains. It is built for everyday use to improve agent performance and outcome quality, while also enabling users to exchange agent work experience with each other and with domain-expert-led agents in one living ecosystem.

Install

npx agent-apprenticeship init

npm install -g agent-apprenticeship
apprentice init

The installed command is:

apprentice

The long-form command also remains available:

agent-apprenticeship

Quickstart

apprentice init
apprentice settings
apprentice run "Create a short market map for AI procurement tools."

Runs print the artifacts path and Contribution Bundle path.

apprentice ecosystem contribute <bundle_path>

Public ecosystem:

https://github.com/Forsy-AI/agent-apprenticeship

Apprentice Agents

Selected v0 Apprentice Agents:

Codex
Cursor
Claude Code
OpenClaw
OpenCode
Hermes Agent
Custom

Agent Apprenticeship auto-detects installed CLIs. If multiple are detected, choose one during setup.

Custom lets you provide a command template:

apprentice configure agent custom --command-template "my-agent run --workspace {workspace} --prompt-file {prompt_file}"

Mentor Model Providers

Store local keys in:

~/.agent-apprenticeship/.env.local

Example:

OPENAI_API_KEY=""
ANTHROPIC_API_KEY=""
GEMINI_API_KEY=""
OPENROUTER_API_KEY=""

Configure:

apprentice configure model
apprentice doctor

Mentor Modes

apprentice run "..." --mentor-mode model-assisted
apprentice run "..." --mentor-mode expert-led
apprentice run "..." --mentor-mode hybrid

model-assisted: Mentor Model Provider handles the mentor loop.
expert-led: human expert checkpoints guide the mentor loop.
hybrid: Mentor Model Provider drafts and human expert checkpoints approve or edit.

Ecosystem Search

The public ecosystem brings together the seed dataset and community-contributed agent experience packages in one searchable network.

Explore ecosystem experience:

apprentice ecosystem list
apprentice ecosystem search cloud
apprentice ecosystem inspect aa-seed-task-501
apprentice ecosystem pull aa-seed-task-501

The seed dataset is included under:

seed_dataset/

Ecosystem Learning

Pulled ecosystem experience can be used directly or turned into Experience Packs:

apprentice learn create aa-seed-task-501
apprentice learn preview <pack_id>
apprentice learn replay <pack_id>
apprentice learn keep <pack_id>
apprentice run "Create a related incident response checklist." --experience-pack <pack_id>
apprentice learn revert <pack_id>

Use active packs explicitly:

apprentice run "..." --use-active-experience-packs
apprentice run "..." --no-experience-packs

Contribution Bundles

Runs produce Contribution Bundles.

Contribute one to the public ecosystem:

apprentice ecosystem contribute <bundle_path>
apprentice bundle contribute <bundle_path>

Public ecosystem:

https://github.com/Forsy-AI/agent-apprenticeship

Ecosystem Auto-Share

Default mode is Manual.

apprentice ecosystem configure --repo Forsy-AI/agent-apprenticeship
apprentice ecosystem configure --auto-share manual
apprentice ecosystem configure --auto-share ask
apprentice ecosystem configure --auto-share automatic
apprentice ecosystem status

Requirements:

GitHub CLI installed
gh authenticated
ecosystem repo configured

Search, Inspect, Pull

Discover and export ecosystem experience:

apprentice ecosystem search <query>
apprentice ecosystem inspect <id>
apprentice ecosystem pull <id>

Public Repo Structure

seed_dataset/
ecosystem/
ecosystem/contributions/
schemas/
examples/

Development Commands

.venv/bin/python -m pytest -q tests
PYTHONPATH=src .venv/bin/python -m compileall -q src tests scripts examples
bash scripts/export_public_repo.sh