427 skills · sorted by relevance
Runs iterate-until-pass loops with ralph-worker agents in a worktree. Use when running [ralph]-marked tasks or looping until verify passes.
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Inspect and commit local git work, or branch into an isolated worktree.
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The Arbor research-coordinator protocol: the OBSERVE -> IDEATE -> SELECT -> DISPATCH -> DECIDE cycle over a durable Idea Tree. Preloaded automatically on /auto-research sessions. The coordinator never edits code or runs commands — executors do that in isolated worktrees; the coordinator steers the tree with idea_tree / dispatch_experiments / merge_experiment.
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Inspect Orchestra projects and tasks, assign workers, queue planning, approve exact plans only on human instruction, request replanning with feedback, show stored PR linkages, reconcile receipts, and scope native agent/skill authoring. Orca-managed worktrees use the separate Orca CLI skill.
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Choose, reuse, restore, park, or clean up Git workspaces while preserving work and host ownership. Create isolation only when it resolves a real conflict; inspection does not authorize creation or deletion.
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当需要开始与当前工作区隔离的功能开发或执行实现计划之前使用——创建具有智能目录选择和安全验证的隔离 git 工作树
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Enable a Skia + Dawn GPU build of Pulp (MacGpuWindowHost, Skia Graphite). Covers the prebuilt skia-builder binaries, the headers-only fresh-worktree trap, reusing another checkout's cached libs via SKIA_DIR, FindSkia layouts, verifying PULP_HAS_SKIA / MacGpuWindowHost, and the raster-fallback + GPU-wedge gotchas. Use whenever GPU rendering "doesn't work" or a build silently came up CPU-only.
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Forge Modular's generator, patch checker, module pack and Forge-worktree seam — the traps that make green results untrue
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Use OpenClaw Manager (OCM) safely and correctly for OpenClaw environment lifecycle work, runtime installation/builds, release-shaped local builds, upgrades, migration/adoption, cloning existing user state, service supervision, gateway logs, dev worktrees, plugin testing, model/provider smoke tests, TUI/dashboard checks, cleanup, and concise reporting. Use whenever Codex is asked to use OCM, manage OpenClaw envs/runtimes/services, test OpenClaw with OCM, reproduce existing-user or new-user flows, or avoid breaking user state while working with OpenClaw.
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Orchestrate AI coding agents (Claude Code, Codex, OpenCode) in isolated sandboxes using the @ai-hero/sandcastle SDK. Use when the user needs to (1) run agents AFK in Docker/Podman containers, (2) build multi-agent pipelines with plan-execute-review patterns, (3) run parallel agents on separate worktrees, (4) create iterative agent loops with maxIterations, (5) extract structured output from agent runs, (6) set up sandcastle in a new or existing project, or (7) write prompt files with template args and shell expressions.
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Orchestrate unattended resolution of open GitHub issues - triage by complexity, dispatch parallel worker agents into isolated worktrees, review their diffs, open PRs, and monitor CI and CodeRabbit until green. Use when asked to work through open issues autonomously or put Claude on auto-pilot.
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Standard collaboration patterns for all squad agents — worktree awareness, decisions, cross-agent communication
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Execute a Prometheus work plan in Codex with Boulder state, evidence ledger updates, worktree discipline, parallel subagents, and Stop-hook continuation. Use after planning when the user says start work, execute plan, continue plan, resume plan, or asks to run a .omo/plans plan.
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Orchestrate multi-agent coding tasks via Claude DevFleet — plan projects, dispatch parallel agents in isolated worktrees, monitor progress, and read structured reports.
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Expert in Git workflows, conventions, and patterns for modern development teams and AI agents. Activate on: branching strategy, commit conventions, git hooks, pre-commit, husky, lint-staged, trunk-based development, git worktree, monorepo git, PR review workflow, conventional commits, git workflow. NOT for: CI/CD pipelines (use github-actions-pipeline-builder), repository hosting (use devops-automator), multi-agent orchestration (use multi-agent-coordination).
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A gate before git push / deploy — assembled from your own tools (secret-grep + slop-scan + code-review + build/compile + optional worktree isolation), so AI junk (slop / bugs / secrets / uncompiled code) never reaches a remote or a production server. Turns "I hope it's clean" into a verifiable criterion. Branches: web/OSS (git push/PR) vs deploy-to-server service. Triggers — "check before push", "clean push", "gate before push", "finalize before commit", "run before deploy".
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Use lane in this repository when the user asks to create or work in an isolated worktree.
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Prepare GEODE worktrees, Korean PRs, CI-gated merges, and guarded cleanup. Use for repository branch, commit, PR, merge, or release work; apply only the stages the user authorized.
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Grind through ready beads in priority order by running several issues at once, each in its own isolated git worktree managed by worktrunk (`wt`), then merging the finished branches back one at a time. Use when asked to work the beads queue in parallel, to run N issues concurrently, or when a serial grind is too slow and the ready issues are independent.
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Applies local lessons to every use of the Orca CLI (orca-ide, orca-dev). Use alongside the upstream orca-cli skill whenever the Orca CLI is needed, including before creating a branch worktree or asking the user for feedback on a change before committing while running inside Orca.
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Rebases every local branch of a fork onto a moved upstream, flags the ones upstream has superseded, and rebuilds the mixdown branch that combines them. Use after fetching a fork's upstream and finding it has advanced far, been force-pushed, or rewritten its history; when several stacked or sibling branches all need bringing forward at once; when a branch was cut from a mixdown and now carries merge commits it should not have; or when asked to rebase all branches, re-mix, or bring a whole worktree set up to date.
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Autonomously improve a real artifact (code, training recipe, agent harness, data pipeline, prompt) against an objective and an evaluator, using Hypothesis Tree Refinement (HTR) from the Arbor paper. Use this whenever someone wants to iteratively optimize something over many experiments without overfitting — e.g. "get my model's eval score up", "improve this agent/harness", "tune this pipeline", "beat the baseline on this benchmark", "run a search over approaches and keep the best", "do an MLE-bench / Kaggle-style optimization", or any long-horizon "make this artifact better and don't just memorize the dev set" task. Trigger it even when the user doesn't say "Arbor" or "hypothesis tree" but describes repeated experiment-and-evaluate loops, branching exploration of competing ideas, or worries about a dev/test gap. Runs Claude itself as the coordinator with subagent executors in isolated git worktrees; for the standalone `arbor` CLI tool see references/arbor-upstream.md.
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Set up a parallel agent team for COMPLEX tasks: creates worktree structure, an ownership map, and an initialized task queue. Use when a task is decomposed into parallel subtasks.
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Coordinate staged or parallel jobs across coding-agent runtimes and subagents: routes by capability/risk, isolates writers in worktrees, arbitrates results. NOT for a single-agent task (mk:cook).
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