Loading...
Loading...
Found 48 Skills
Explore a codebase with parallel Haiku agents. Modes - --fast (1 agent), default (3), --deep (5). Use when user says "learn [repo]", "explore codebase", "study this repo".
This skill should be used when the user asks about new features, recent changes, or updates in Claude Code — for example "what's new in Claude Code?", "Claude Code changelog", "what did I miss in Claude?", "any recent updates?", "tell me about new Claude features", or "what's changed since version 1.0.30?". It fetches the official changelog, filters for notable features (excluding bug fixes), researches each feature for deeper context on Anthropic's website, and presents mini-article summaries. Supports both automatic tracking (since last check) and explicit version queries.
Decomposes complex, multi-day tasks into optimized milestones using parallel reviewer agents (ultraplan). Spawns 5 independent reviewers that analyze the problem from different angles, then synthesizes their findings into a milestone dependency DAG. Triggers when the user says "plan milestones", "break this into milestones", "ultraplan", or when long-run harness needs milestone generation.
Process large codebases (>100 files) using the Recursive Language Model pattern. Orchestrates parallel sub-agents to map-reduce across files without context rot. Use when: analyzing large repositories; auditing security or auth across many files; finding patterns across 50+ files; processing large log files or data dumps
Enhance a plan with parallel research agents for each section to add depth, best practices, and implementation details
Use git worktrees to run multiple coding agents in parallel on one repo without collisions. Use when starting a task in a shared repo, when the user says "worktree", "parallel agents", "one worktree per task", or when agents keep overwriting each other's changes. Covers creating worktrees, making them as complete as the main checkout (.env files, dependencies, databases, ports), merging back, and cleanup.
Show status of all features in .dev/. Scans feature folders using parallel agents, generates a status report, and offers to archive completed features.
Design exploration with parallel agents. Use when brainstorming ideas, exploring solutions, or comparing alternatives.
Explore a codebase with parallel agents, then hand off findings.
Implementiert alle offenen GitHub Issues eines Repositories vollautomatisch in einem Rutsch. Issues, die voneinander unabhängig sind, werden parallel über Subagents abgearbeitet; abhängige Issues laufen sequenziell. Jede Implementierung wird per `/tdd` test-getrieben entwickelt, über Playwright-MCP verifiziert, bei Fehlern mit `/diagnosing-bugs` analysiert und nach Caveman-Prinzipien (`/caveman`) vereinfacht. Erfolgreiche Implementierungen werden committet, der User bekommt erst nach Abschluss aller Issues eine Sammelmeldung. Nutze diesen Skill IMMER, wenn der User sagt "implementiere alle issues", "alle gh issues", "issues aus github abarbeiten", "batch implementation", "parallel issues bearbeiten", "alle offenen tickets" oder ähnliches — auch ohne explizite Nennung von Playwright/TDD/Caveman, da diese Werkzeuge zum Standard-Workflow gehören.
Decompose large-scale changes into independent units and spawn parallel agents in isolated worktrees. Use for migrations, refactors, codemods, and any change touching 10+ files with the same pattern.
Orca（stablyai/orca）をworktreeとagent terminalのfrontendとして使うprojectで、Orcaを導入・設定する時、またはOrca上でworktreeを作る・消す・agentを並列に動かす時に使用する。Orcaを使わないprojectでは使わない。