factory

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Domain-agnostic multi-agent software design and evolution harness

plugin 62 stars 26 forks Updated today MIT

Install

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Bundles

Everything this plugin ships — skills, agents, commands, hooks, and MCP servers it bundles.

Skills (6)

AI & Automation Solid

factory

Launch the Factory CEO agent to autonomously evolve any software project through systematic experimentation. Detects project state, spawns specialist agents, runs evals, and archives learnings.

62 Updated today
akashgit
AI & Automation Listed

implement

Build a specific feature or improvement using Factory's multi-agent system. Runs the Factory CEO in focus mode to study the codebase, generate a hypothesis, build the change, review it, and evaluate the result. Use when the user says 'implement X', 'build X', 'add X feature', or wants autonomous multi-agent development on a specific task.

62 Updated today
akashgit
AI & Automation Solid

pipeline-subagents

Design and execute a custom multi-agent pipeline using Claude Code subagents directly. Spawns researcher, builder, etc. via the Agent tool with native parallel and background execution. Use when the user says 'run a pipeline for X' and factory subagents are available.

62 Updated today
akashgit
AI & Automation Solid

pipeline

Design and execute a custom multi-agent pipeline for any goal. Analyzes the goal, selects appropriate specialist agents, designs a DAG of steps with dependencies, and executes them via factory CLI with gate decisions between steps. Use when the user says 'run a pipeline for X', 'orchestrate X', or wants a custom multi-agent workflow.

62 Updated today
akashgit
AI & Automation Listed

status

Show the current Factory status for this project, including project state, experiment history, eval scores, and active backlog. Use when the user asks about the factory status, project state, or experiment history.

62 Updated today
akashgit
AI & Automation Listed

study

Analyze the current codebase using Factory's observation engine. Generates a report covering code quality, eval scores, open issues, backlog items, observability coverage, and improvement opportunities. Use when the user wants to understand the state of their project before making changes.

62 Updated today
akashgit

Quality Score: 76/100

Stars 20%
60
Recency 20%
100
Manifest 20%
100
Documentation 15%
0
Issue Health 10%
50
License 10%
100
Description 5%
100

Details

Author
akashgit
Repository
akashgit/remote-factory
Created
4 months ago
Last Updated
today
Language
Python
License
MIT