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orchestrating-parallel-agents

Spawns multiple AI coding agents to work on related GitHub issues concurrently using git worktrees. Use when breaking down a large feature into multiple issues, running parallel agents with --print flag, or managing wave-based execution of related tasks.

DeepseekModel キュレーション済みスキル 品質 良好 · 48 v1.0.0

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ダウンロード .skill 標準形式。system_prompt と model_config を収録し、任意の Agent で利用可能
.skill ファイルの system_prompt フィールドの実際の内容。
name orchestrating-parallel-agents description Spawns multiple AI coding agents to work on related GitHub issues concurrently using git worktrees. Use when breaking down a large feature into multiple issues, running parallel agents with --print flag, or managing wave-based execution of related tasks. allowed-tools Bash, Read, Write, Edit, Glob, Grep, Task, TodoWrite Orchestrating Parallel Agents Spawn multiple Claude agents to work on related issues concurrently using git worktrees. Philosophy Issues ARE the prompts - Write issues with enough context for autonomous work Maximize parallelism - Group independent work into waves Fail fast - Complete git/PR manually if agents can't Trust but verify - Review diffs, resolve conflicts manually Workflow Checklist Copy and track progress: Parallel Agent Orchestration: - [ ] 1. Break feature into issues (1-3 files each) - [ ] 2. Organize into waves (independent → dependent) - [ ] 3. Pre-approve git permissions in settings.local.json - [ ] 4. Spawn wave with --print flag - [ ] 5. Monitor progress - [ ] 6. Complete stragglers manually - [ ] 7. Merge PRs (rebase between same-file conflicts) - [ ] 8. Cleanup worktrees Issue Template Each issue should be completable in isolation: ## Problem What's broken or missing. ## Solution High-level approach. ## Files to Modify - `path/to/file` - what changes ## Implementation Code snippets or pseudocode. ## Acceptance Criteria - [ ] Testable outcomes Key: Include file paths and code examples. Agents work best with concrete starting points. Wave Organization Wave 1: Independent changes (no shared files) Wave 2: Changes that may touch same files (expect conflicts) Wave 3: Integration/testing (depends on all above) Rule: Same-file issues go in different waves OR same agent. Pre-approve Permissions Add to .claude/settings.local.json for non-interactive --print mode: "Bash(git -C /absolute/path/to/worktree add:*)" , "Bash(git -C /absolute/path/to/worktree commit:*)" , "Bash(git -C /absolute/path/to/worktree push:*)" Spawn Agents for issue in 101 102 103; do (claude -- print "/worktree-issue $issue " > "issue- ${issue} .log" 2>&1) & done Monitor ps aux | grep "claude.*worktree" | wc -l # Running agents git worktree list # Worktrees created tail -f issue-*. log # Live logs Complete Stragglers If agent finishes code but fails on git: git -C <worktree> add -A git -C <worktree> commit -m "feat: description" git -C <worktree> push -u origin <branch> gh pr create -- head <branch> --title "..." --body "Closes #N" Merge with Conflicts gh pr merge N --squash --delete-branch If conflicts after prior merges: cd <worktree> && git fetch origin main && git rebase origin/main # resolve conflicts git push --force-with-lease Cleanup git worktree remove <path> git branch -D <branch> git worktree prune Quick Reference Tip Why 1-3 files per issue Higher success rate Include "Files to Modify" Agents find code faster Backend-first waves Fewer frontend conflicts Merge same-file PRs sequentially Rebase between each Problem Solution Agent stuck on permissions Complete git manually Merge conflict Rebase, resolve, force-push Agent went off-scope Reject PR, clarify issue Too many conflicts Smaller waves, sequential merge
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ダウンロードした .skill に含まれるフィールド。
フィールド 説明
formatフォーマット識別子(skill/v1)
skill_idスキル固有 ID
nameスキル名
versionバージョン
description説明
categoryカテゴリ(配列)
trigger_wordsトリガーワード
tagsタグ
sourceソース
source_urlソース URL(本ページ)
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system_promptシステムプロンプト本文
model_configモデル設定:provider / model / temperature / max_tokens / top_p
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.skill 標準形式。system_prompt と model_config を収録し、任意の Agent で利用可能 ダウンロード
.skillpro 拡張形式。scripts / tools / dependencies / hooks を含む ダウンロード
.json 純粋な JSON 出力。system_prompt とモデル設定のみ ダウンロード
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