By gunesbizim
Autonomous development pipeline — auto-configures MCP servers, scaffolds project-aware Claude Code skills, and drives ticket-to-PR workflows
Use when the user is debugging a regression, investigating unexpected behaviour, or wants to know the full change history of a component. Examples: "why did this break after the last deploy?", "what changed in the auth module recently?", "trace all changes to OrderService"
Use when the user wants to index a repository into git-memory, start using git-memory on a new project, or re-index after significant history. Examples: "index the lokumcu repo", "set up git memory for this project", "re-index everything"
Use when the user asks about why code was written a certain way, wants to find commits related to a bug, feature or module, or needs historical context before editing. Examples: "why does the payment module use a state machine?", "what commits touched auth?", "find all discount-related bug fixes"
Use when the user wants to check what is indexed, how many commits are in memory, or whether git-memory is set up correctly. Examples: "is git memory set up?", "how many commits are indexed?", "check git memory status"
Use when the user needs to run GitNexus CLI commands like analyze/index a repo, check status, clean the index, generate a wiki, or list indexed repos. Examples: "Index this repo", "Reanalyze the codebase", "Generate a wiki"
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Point it at your code. It reads your project, then sets up your AI coding assistant to work your way — with the right commands, the right helpers, and guardrails so it can't make a mess.
Imagine you get a brand-new robot helper. Out of the box, the robot is smart but it doesn't know your house — where the kitchen is, which cup is yours, that you never wear shoes inside.
Agent Smith is the person who shows the robot around your house. It walks through your project, notices how things are done ("ah, this is a Java kitchen, the tests live here, you tidy up with this tool"), and then hands the robot a little instruction card so it helps you the way you already work — instead of guessing and doing it wrong.
It also puts up a few safety gates ("don't touch the stove," "always wash the cup after") so the robot can help on its own without breaking anything. You're still in charge — the robot asks before doing the big, scary stuff.
That robot is Claude Code (Anthropic's AI coding assistant). Agent Smith is the setup crew that makes Claude Code instantly useful in your repository.
A general AI assistant doesn't know your project. So it:
pytest on a Java project — a real bug this tool was built to kill),You could hand-write all that setup yourself for every repo. Agent Smith does it for you, automatically, by reading your actual project — and keeps it honest: if it can't tell what something is, it says so instead of guessing.
One command turns a plain repository into a Claude-Code-ready workspace with:
| Thing it installs | What it's for |
|---|---|
Slash commands (/as-backend, /as-test, /as-ship, …) | One-word shortcuts for everyday jobs, pre-loaded with your stack |
| Skills (review, test, docs writers — plus fable-mode) | Detailed playbooks the assistant follows for specific tasks |
| MCP servers (gitnexus, git-memory, serena, …) | Give the assistant memory: code structure, git history, symbol search |
| Hooks (session start, pre-tool, stop) | Automatic checks that run around the assistant's actions |
| Sentrux quality gate | A guardrail that blocks changes which make the architecture worse |
A managed CLAUDE.md section | A living cheat-sheet of every command and skill, refreshed on each run |
All of it is tailored to the stack Agent Smith detected — not a generic template.
You need Node 20+ and the claude CLI on your PATH (for the smartest setup; it still works without it, just less customized).
# from the root of the project you want to set up
npx @gunesbizim/agent-smith init
That's it. Restart Claude Code and try a command like /as-backend "add a health endpoint".
Want to look before you leap?
npx @gunesbizim/agent-smith analyze # just print what it detects, change nothing
┌───────────┐ ┌───────────┐ ┌──────────┐ ┌──────────┐
your │ 1. DETECT │ ──▶ │ 2. ADAPT │ ──▶ │3. INSTALL│ ──▶ │4. OPERATE│
repo │ the stack │ │ skills & │ │ MCPs, │ │ commands,│
│ │ │ docs to it│ │ hooks, │ │ guarded │
└───────────┘ └───────────┘ │ gate │ │ pipeline │
└──────────┘ └──────────┘
Agent Smith gathers evidence the project declares about itself — build manifests and CI files (pom.xml, build.gradle, package.json, go.mod, Cargo.toml, pyproject.toml, .github/workflows/…, Makefile, …) across every module. It then synthesizes a StackProfile: the language, framework, ORM, database, and the real commands to test/lint/format/migrate.
claude CLI is present, an LLM pass reads the evidence and classifies the stack — so it covers essentially any language without a hardcoded list.none — never filled in with a borrowed default. (This is the honesty rule that stops a Java project from being told to run ruff/pytest.)npx claudepluginhub gunesbizim/agent-smithTrack and report Claude token usage from local logs and the Anthropic Admin API
Comprehensive skill pack with 66 specialized skills for full-stack developers: 12 language experts (Python, TypeScript, Go, Rust, C++, Swift, Kotlin, C#, PHP, Java, SQL, JavaScript), 10 backend frameworks, 6 frontend/mobile, plus infrastructure, DevOps, security, and testing. Features progressive disclosure architecture for 50% faster loading.
Upstash Context7 MCP server for up-to-date documentation lookup. Pull version-specific documentation and code examples directly from source repositories into your LLM context.
Harness-native ECC operator layer - 67 agents, 271 skills, 92 legacy command shims, reusable hooks, rules, selective install profiles, and production-ready workflows for Claude Code, Codex, OpenCode, Cursor, and related agent harnesses
Develop, test, build, and deploy Godot 4.x games with Claude Code. Includes GdUnit4 testing, web/desktop exports, CI/CD pipelines, and deployment to Vercel/GitHub Pages/itch.io.
Access thousands of AI prompts and skills directly in your AI coding assistant. Search prompts, discover skills, save your own, and improve prompts with AI.
Upstash Context7 MCP server for up-to-date documentation lookup. Pull version-specific documentation and code examples directly from source repositories into your LLM context.