31 skills · sorted by relevance
Coordinate groups of AI agents across multiple GitHub repositories. Analyze dependencies, organize shared updates and refactoring, run tests, and create linked pull requests so related projects can be changed together.
Coordinate changes across multiple GitHub repositories with teams of AI agents. Align package versions, synchronize documentation, standardize project structures, and organize integration tests and pull requests for updates that affect several projects.
Multi-repository coordination, synchronization, and architecture management with AI swarm orchestration
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Multi-repository coordination, synchronization, and architecture management with AI swarm orchestration
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Multi-repository coordination, synchronization, and architecture management with AI swarm orchestration
The English summary is being prepared. Showing the original description.
Multi-repository coordination, synchronization, and architecture management with AI swarm orchestration
The English summary is being prepared. Showing the original description.
Multi-repository coordination, synchronization, and architecture management with AI swarm orchestration
The English summary is being prepared. Showing the original description.
Multi-repository coordination, synchronization, and architecture management with AI swarm orchestration
The English summary is being prepared. Showing the original description.
Multi-repository coordination, synchronization, and architecture management with AI swarm orchestration
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Agent skill for multi-repo-swarm - invoke with $agent-multi-repo-swarm
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Coordinate changes across multiple GitHub repositories, align package versions, synchronize documentation, and run integration tests. The skill also guides shared repository templates and organizes AI agents to handle related development tasks.
Manage multiple apps and shared packages in one repository. Analyze dependencies and change impacts, limit builds and tests to affected packages, configure caching, and plan repository consolidation while preserving Git history.
Make AI truly understand large codebases: for multi-repository, multi-microservice projects that have evolved over years, run architecture reverse-engineering + a Graph RAG graph + multi-language AST to compress a huge codebase into a structured knowledge base, where every conclusion traces back to a code line and every relation carries a confidence label. Suited to projects with 10+ repositories or microservices that AI cannot understand globally by reading the code directly. Triggers: architecture analysis, architecture reverse-engineering, codebase knowledge base, code-to-knowledge, architecture wiki, large multi-repo codebase. Loaded on demand by the teamai discovery stub.
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Builds multi-repo context hubs and compiled markdown knowledge maps. Use when profiling repo portfolios or assembling LLM-ready cross-repo knowledge bases.
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Multi-repository coordination, synchronization, and architecture management with AI swarm orchestration
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Make every team AI native — TeamAI syncs a team's AI skills, rules, docs and env across AI coding tools. Use when the task operates on team-shared AI configuration or team knowledge: setting up a team repo, joining one, managing members, syncing with pull or push, or checking team status. Also use to build or query a codebase knowledge base for a large multi-repo project (architecture analysis, architecture reverse-engineering, code-to-knowledge, team-wiki-codebase, architecture wiki), and to share what a session taught you back to the team (share session learnings, contribute a learning, share what I learned with my team), including after a friction reminder. Triggers include "set up teamai", "join the team repo", "sync team skills", "team wiki", "share what I learned", and running /teamai. Talking about a team needs no skill; operating on what the team shares does.
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Extract and score leads from GitHub repositories by analyzing stars, forks, issues, PRs, comments, and contributions. Produces unified multi-repo CSV with deduplicated user profiles. No paid API credits required.
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Manage and optimize monorepos with Turborepo, Nx, pnpm workspaces, and Changesets. Use when working in monorepos, running impact analysis, optimizing build times with remote caching, migrating from multi-repo, or coordinating publishing.
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Use when deploying changes to staging across relay, relay-dashboard, and relay-cloud repos - coordinates multi-repo branch syncing using git worktrees, automatically triggers staging deployments via GitHub Actions
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Manage git worktrees across any repository with the `gwm` Rust binary (CLI + ratatui TUI). Use when the user asks to create / list / remove / bootstrap / switch / link worktrees, run a command across worktrees (`gwm exec`) or reclaim build artifacts (`gwm clean`), materialise a PR into a worktree (`gwm review`), drive a multi-repo workspace (`--workspace`), run the JSON daemon / statusline (`gwm daemon`, `gwm statusline`), list or pin AI-agent sessions per worktree (`gwm agents`, Claude Code / Codex / opencode / Mistral Vibe detection), seed config from a preset (`gwm init --preset`), diagnose with `gwm doctor`, drive tmux/zellij, or wire `gcd` via `gwm shell-init`. Also covers multi-forge (#419): GitHub via `gh` **or** GitLab via `glab`, the `forge` / `[forge_hosts]` keys, and `gwm trust add`. Triggers on `gwm`, `gwq`, `git worktree`, `.gwm.toml`, `forge`, `forge_hosts`, `glab`, `gwm trust add`, GitLab MR, `gwm create`, `gwm list`, `gwm exec`, `gwm clean`, `gwm review`, `gwm daemon`, `gwm statusline`, `gwm agents`, `gwm note`, `gwm bootstrap`, `gwm doctor`, `gwm switch`, `gwm tmux`, `gwm zellij`, `gwm link`, `gwm status`, `gwm shell-init`, `gcd`, `feat/#`, `fix/#`, GitHub issue/PR linking on a worktree.
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Context-driven AI development with AGENTS.md, repo knowledge bases, Claude Code, Codex, and Copilot. Use when adopting repo-native AI workflows or multi-repo setups.
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Repo Updater - Multi-repo synchronization with AI-assisted review orchestration. Parallel sync, agent-sweep for dirty repos, ntm integration, git plumbing. 17K LOC Bash CLI.
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Produce animated source control visualizations using Gource. This skill handles installation of Gource and ffmpeg, detection of repository metrics, preset-based configuration, single and multi-repo log generation, ffmpeg video encoding pipeline, headless rendering for server environments, caption generation from git tags, GitHub avatar resolution, and GSD output delivery. Use this skill whenever the user wants to visualize repository history, create a code evolution video, see project timeline animations, generate Gource videos, combine multiple repos into one visualization, or produce any kind of source control visualization. Also trigger when the user mentions "Gource", "repo visualization", "code history video", "project evolution animation", or asks to "show me what we built".
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Use when the user wants one-time repository setup for tracker, triage labels, and domain conventions. Not for ongoing triage, issue creation, or multi-repo setup.
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