#claude-code

Zero-dep agent workflows with structured approval gates and adversarial review.

A multi-agent context, rules, and hooks boilerplate generator. With a single command, it scaffolds conventions, namespaced skills, stack-appropriate settings, and interactive guardrails for seven major AI coding environments, matching each agent's native file formats and capability profiles.

Quality-gated autonomous mission completion loop for Claude Code and Codex (plan, execute, review, score, iterate).

Ten agent sessions, one screen. A tmux-based TUI for Claude Code, Codex and opencode — see which agent is waiting on you, give each its own git worktree, and resume after a reboot.

Claude Code skills for git workflows, GitHub automation, security audits, code refactoring, and project tooling

Self-hosted web dashboard for supervising multiple Claude Code AI sessions in tmux. Live terminals, real-time git diffs, file browser, todo lists, prompt templates, and mobile PWA support. Micromanage your AI interns from any device.

Spec + Test Driven Development — markdown-first methodology kit for AI coding agents. The docs edit is the spec; tests gate behavior; working artifacts are never committed.

Leave notes in the margins of your repo's docs then let your AI agent apply them, resolve the threads, and journal what changed & why.

the trust layer for agent memory

Опис репозиторію не опубліковано.

The intentional memory layer for your AI agents.

Local, human-in-the-loop message bus for coordinating parallel AI coding-agent sessions on one machine

Local TUI to track Claude Code usage, costs, and tasks (Go + Bubbletea + SQLite)

Correction-first persistent memory for AI agents. MCP server + SDK + CLI. Compounds across sessions.

Local‑first MCP server for multi‑repository semantic code search with Qdrant and llama. Turns your entire workspace into private context for AI coding assistants like Claude Code, Codex, Cursor, Copilot, Antigravity and Windsurf.

🩺 Doctor for your repo's AI harness — audit, merge & drift-guard scattered agent configs (AGENTS.md / CLAUDE.md / .cursorrules) into one source of truth. Real evals: 6/28 → 28/28 correct, −27% latency. Field-tested on react, vscode, n8n + 11 more. Claude Code · Codex · Cursor · Gemini

Claude Skills for Optima AI Development Team - 开发团队共享的 Claude Code 技能集合

Minimal LLM API reverse proxy for Claude Code, Codex CLI & Gemini CLI — YAML routing, hot reload, and automatic provider failover. 极简 LLM API 反向代理：面向 Claude Code / Codex CLI / Gemini CLI，支持 YAML 配置、多上游优先级与自动故障转移。

An alternative to Github Agentic Workflows when you cannot use them

Поиск по коду для ИИ-агентов: 32 инструмента MCP, индекс на SQLite, один бинарник без зависимостей. Разбирает выгрузки 1С:Предприятие — Конфигуратор и EDT; конфигурация на 88 тыс. файлов индексируется за 6 минут, ответ на запрос — 10 мс. Code index MCP server: tree-sitter AST for 14 languages, 20 universal tools + 12 for 1C/BSL.

AI-native service workbench: MCP server + shared daemon for Claude Code, Codex, and Gemini. CLI, TUI, and web dashboard for running services, logs, git, and databases.

Опис репозиторію не опубліковано.

Two-layer enforcement (pre-commit hook + CI mirror) for small teams using AI agents. Catches debug leaks, file growth, secrets, and forbidden patterns before they merge, and scaffold-doctor tells you when a guardrail is installed but not actually running.

swarmdo — self-contained AI agent orchestration for Claude Code (swarmdo.com)

CLI & library to faithfully translate coding agent customizations across harnesses

Multi-agent orchestration via MCP. Persistent memory, inter-agent messaging, goal cascade, context budget pruning. One binary, zero config.

Read-only-by-default MCP server for PostgreSQL. Query, introspect schemas, explain plans, health checks.

One zero-dependency CLI for all your MCP tools and agent skills. 99.2% fewer tokens on tool discovery, one config for every agent, nothing pre-installed. | 一个零依赖 CLI，管所有 MCP 工具和 Agent 技能。工具发现省 99.2% token，一份配置通吃所有 Agent，原生不预装。227KB，纯 Python 标准库。

Shared memory across your team and your AI agents — with judgment about what's worth keeping.

Convention over configuration for agentic development teams