# agent-feed: Govern AI Coding Workflows in Your Repository This repository profile is provided by osrepos.com, an open source repository discovery platform. Source: osrepos.com Repository profile: https://osrepos.com/repo/fqmyysjjd-agent-feed Generated for open source discovery and AI-assisted research. Agent Feed installs a repository-owned workflow for AI coding tools, with shared instructions, task and review gates, checks, and tool adapters. It suits teams that want consistent, verifiable AI-assisted changes across Codex, Claude Code, and Cursor. GitHub: https://github.com/fqmyysjjd/agent-feed OSRepos URL: https://osrepos.com/repo/fqmyysjjd-agent-feed ## Summary Agent Feed installs a repository-owned workflow for AI coding tools, with shared instructions, task and review gates, checks, and tool adapters. It suits teams that want consistent, verifiable AI-assisted changes across Codex, Claude Code, and Cursor. ## Topics - python - ai-agents - developer-tools - workflow-automation - coding-agent - agent-skills - cursor-rules ## Repository Information Last analyzed by OSRepos: Mon Oct 12 2026 12:00:35 GMT+0100 (Western European Summer Time) Detail views: 1 GitHub clicks: 1 ## Safety Notice OSRepos shares public repositories for knowledge and discovery only. Review source code, dependencies, licenses, and security implications before running or installing anything. ## Content ## Overview Agent Feed is a Python CLI that installs workflow instructions and supporting checks into a code repository. It addresses the fragmentation that occurs when AI coding guidance lives across chat history, tool-specific rules, and scattered project documents. The installed protocol uses `AGENTS.md` as a shared entry point, with rules, skills, project knowledge, verification steps, and adapters for Codex, Claude Code, and Cursor. It is designed for teams that want AI-assisted changes to follow repository-defined scope, decision, review, and handoff practices. ## Key Features - Initializes a repository with `AGENTS.md` and a structured `.agents/` workflow. - Provides thin adapters for Codex, Claude Code, and Cursor, keeping the shared protocol canonical. - Defines task boundaries, decision checkpoints, verification gates, review, and session handoff. - Checks protocol structure, references, scripts, skills, and client adapters. - Supports project-specific constraints and domain knowledge alongside reusable workflow rules. - Manages local and imported skills, with trust checks for external assets. - Includes status, upgrade, adapter sync, and configuration commands in its CLI. ## Use Cases - A team using several AI coding tools wants repository instructions to stay consistent across clients. - Developers want small coding requests to remain scoped and architecture or contract decisions to receive human confirmation. - Teams need completion to include project-defined tests, documentation checks, or review rather than relying on chat claims. - A developer working across long AI sessions wants a concise handoff of active conclusions instead of replaying conversation history. - Maintainers want to add team-specific skills and constraints without replacing a shared workflow foundation. ## Our Take Agent Feed offers a concrete, repository-centered way to govern AI coding, but its quiet recent activity and reliance on one contributor make ongoing maintenance worth checking before adoption. **Good fit if:** - You use Codex, Claude Code, or Cursor and want a common source of workflow guidance in the repository. - Your team values explicit scope, verification, review, and human decision gates for AI-generated changes. - You can run a Python 3.11+ CLI and are comfortable adopting an MIT-licensed project whose work is concentrated in one contributor. **Look elsewhere if:** - You need a hosted service or runtime platform rather than repository-installed workflow files and checks. - You need evidence of ongoing commits or issue and pull-request handling: the project is marked quiet, with no commits or closed issues or merged pull requests in the measured recent period. - Your workflow does not use the supported coding-agent adapters and a shared `AGENTS.md` protocol would add little value. ## Project Health | Signal | Value | |---|---| | Status | **Quiet**: no commits in the last 90 days | | Last commit | 2026-05-09 (5 months ago) | | Commits, last 90 days | 0 | | Releases, last 12 months | 9 (latest v1.1.6, 2026-05-08) | | Contributors | 1 | | Issues closed, last 90 days | 0 | | Pull requests merged, last 90 days | 0 | | Project age | 5 months | Checked on 2026-10-12 with the GitHub API. ## Project Facts - Language: Python - License: MIT - Stars: 4 - Forks: 0 - Topics: agentic-development, agentic-development-environment, agentsmd, ai-coding, ai-coding-agents, ai-workflow, claude-code, claude-md - Archived: no ## What You Need Detected in the repository: - Node.js >=16.0.0 (from package.json) - Python >=3.11 (from pyproject.toml) - A test suite and automated checks on GitHub Actions ## Getting Started Install with one of the supported package managers, then initialize and check the repository: ```sh uv tool install agent-feed agent-feed init agent-feed check ``` See the [README](https://github.com/fqmyysjjd/agent-feed) and [Usage Guide](https://github.com/fqmyysjjd/agent-feed/blob/main/docs/usage-guide.md) for setup options and customization. ## License in Plain Words **MIT** (permissive). - Commercial use: yes - Modify and redistribute: yes - You must keep: the copyright and license notice - Share your changes: no A summary, not legal advice: the LICENSE file is what applies. ## Alternatives - [compound-engineering-plugin](https://osrepos.com/repo/everyinc-compound-engineering-plugin): It packages reusable skills for planning through implementation and captured learnings, rather than installing a repository-owned workflow with shared checks and gates. - [agent-skills](https://osrepos.com/repo/addyosmani-agent-skills): It offers portable engineering workflows for planning, testing, review, and release, while agent-feed centers on a repository-owned setup with tool adapters. - [agent-skills](https://osrepos.com/repo/anyoneanderson-agent-skills): It provides reusable specification, review, testing, and sprint skills, rather than a repository-owned workflow with shared instructions and checks. - [agentic-engineering](https://osrepos.com/repo/affectionatec-agentic-engineering): It emphasizes documentation, session memory, and human-controlled merges, while agent-feed installs shared workflow gates and tool adapters in a repository. | Project | Language | License | Stars | Status | |---|---|---|---|---| | **agent-feed** | Python | MIT | 4 | Quiet | | [compound-engineering-plugin](https://osrepos.com/repo/everyinc-compound-engineering-plugin) | TypeScript | MIT | 25.4k | Active | | [agent-skills](https://osrepos.com/repo/addyosmani-agent-skills) | JavaScript | MIT | 101k | Active | | [agent-skills](https://osrepos.com/repo/anyoneanderson-agent-skills) | Shell | MIT | 2 | Active | | [agentic-engineering](https://osrepos.com/repo/affectionatec-agentic-engineering) | – | MIT | 5 | Quiet | ## Considerations - The measured project status is quiet: there have been no commits in the recent measured period, despite releases during the past year. Release activity does not by itself establish current maintenance. - The project has one contributor, with nearly all contribution activity concentrated there. This creates a maintainer-continuity risk for a workflow teams may depend on. - The CLI requires Python 3.11 or newer. The npm package is a wrapper and also requires Python on the machine. - Agent Feed installs and validates instructions and workflow assets; it is not a replacement for the coding agents themselves or for project-specific test infrastructure.