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Implement pending tasks from an OpenSpec change using its specifications and design documents. The skill updates task checkboxes, confirms progress, supports resuming unfinished work, and pauses when requirements or implementation issues need clarification.
Execute an implementation plan file produced by $draft-plan or $turboplan. Runs pre-implementation prep, then runs $implement to execute the steps and finalize once they are all done. Use when the user asks to "implement plan", "implement the plan", "execute the plan", "run the plan", "implement plans/<slug>.md", "start implementing the plan", or starts a fresh session to implement a previously drafted plan.
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Execute an implementation plan file produced by /draft-plan or /turboplan. Runs pre-implementation prep, then runs /implement to execute the steps and finalize once they are all done. Use when the user asks to "implement plan", "implement the plan", "execute the plan", "run the plan", "implement plans/<slug>.md", "start implementing the plan", or starts a fresh session to implement a previously drafted plan.
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親イシュー配下のサブイシュー（孫以下の全子孫を含む）を依存順を保ちつつ worktree で並列に自動実装・push 前 review・PR 作成・CI 監視・マージ可能状態化まで一括自動化。 「イシューツリーを並列実装」「配下のサブイシューをまとめて実装」「ツリー全体を並列で実装して」「イシュー階層を自動開発」で使用。 per-issue 計画立案（Plan: セッション継承モデル）→実装（Implement: sonnet）の分業。push 前 review（Review 通過後にのみ push・PR 作成して CI を 1 回だけ起動）。 外部チェック構成は args の externalChecks で明示（{"app", "context"} の組で宣言。[] で「なし」を確定して不要待機なし・未指定なら自動マージ停止・slug のみの旧形式は自動マージ fail-closed）。 自動 squash merge は autoMerge: true + externalChecks 明示（全 App の信頼済み context 宣言込み）の opt-in で実行（merge-exec の自己取得再検証 + サーバー側 branch protection 実測が前提。既定 false はマージ可能状態で停止し人間がマージ。サーバー側 workflow サンプル（upstream の docs/implement-issue-tree/auto-merge-sample.yml 参照）+ branch protection への委譲も可）。並列度（parallel）と依存（dependsOn）で実行順を制御。 Phase 単位で厳密に直列化したい場合は phaseGate: true（opt-in。ルート直下の子〔Phase 親〕を sub-issues リスト順に直列化し、前 Phase の全子孫が merged/closed になるまで次 Phase 配下に着手しない。既定 false は現行の post-order 優先度のみ）。 着手できる件数・blocked になる件数を事前に知りたい場合は dryRun: true（何も書かずに見積りだけ返す）。 単一イシューの実装は implement-issue、PR レビューは implement-review-pr を参照。
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Take implementation work through small, independently mergeable pull requests. Use a separate working directory for each PR, record manual QA evidence, write English review descriptions, resolve CI and review findings, then merge and clean up.
Evaluate code against a product requirements document, scoring implementation and tests separately for each acceptance criterion. Produce an evidence-backed final grade, identify gaps, and compare implementations using a fixed checklist and scoring method.
Turn specifications and designs into working code using test-driven development: write failing tests, implement enough code to pass, then refactor. The workflow also covers error handling, performance improvements, documentation, and coordinated changes across components.
Implement pending tasks from an OpenSpec change, a planned set of development work. The skill reads relevant specifications and design files, makes focused code changes, and updates task completion as work progresses.
Turn an agreed specification or ticket into a checklist with specific tests or commands for each requirement. Implement the work, run the checks, and have a separate agent verify the entire feature.
Plan and implement features with a workflow that adapts to their complexity. It connects testable requirements to tasks, tests, and small commits, then checks the finished work against the specification through an independent verification pass.
Implement pending tasks from an OpenSpec change, a planned set of development work. The skill reads relevant specifications and design files, makes focused code changes, and updates task completion as work progresses.
Run [implement-spec](../implement-spec/SKILL.md) with Codex doing the implementation passes while you orchestrate, integrate, and review. Use when the user asks to implement a spec with Codex, or to run implement-spec with Codex as the implementer.
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承認済みの実装計画（Plan）を Agent Team で並列に実装するスキル。 Plan をタスクに分割 → 依存関係を設定 → Wave ごとに並列エージェントを起動 → 完了を待って次の Wave → 最後にビルド＆テスト検証。 team-plan スキル（調査→計画）の後に使う「実装実行フェーズ」。 Use when: 計画を並列に実装したい、チームで実装を進めたい、 Wave 実行で効率よくコードを書きたい。 Triggers: "team implement", "チームで実装", "並列実装", "plan を実装して", "wave 実行", "team-implement", "エージェントで実装", "実装フェーズ", "implement the plan"
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エージェントを長時間稼働させて大きな実装タスクを完遂するためのスキル。 TODO ファイル (.md) を管理しながら、高レベル TODO → 細かい TODO に分解 → 実装 → サブエージェントによるレビュー → 不足分の TODO 追加 のサイクルを回す。 コンテキストが大きくなっても TODO ファイルが状態の真実の源泉として機能するため、 長時間・大規模な変更でも迷子にならずに着実に完遂できる。 team-plan や team-implement とは異なり、1人のメインエージェントが逐次的に実装し、 各段階をレビューエージェントが品質検証する。 Use when: 大きな実装タスクを段階的に進めたい、エージェントに長時間任せたい、 実装中に TODO を追加しながら進めたい、各ステップの品質をサブエージェントにレビューさせたい、 長時間の実装を構造化したい、放置しても安心して任せられる実装フローが欲しい。 Triggers: "long-run", "段階的に実装", "TODO駆動で実装", "大きな実装", "ステップバイステップで実装", "レビューしながら実装", "long run implement", "実装を進めて", "大規模実装", "iterative implement", "長時間実装", "エージェントに任せて", "放置で実装"
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Implement work described in a specification or tickets, checking types and running tests along the way. Review the completed changes with the code-review skill, then commit the implementation to the current branch.
Create an implementation plan grounded in code relationships and verified source files, with proposed changes, test scenarios, risks, and a structured handoff for an implementation agent. It can also revisit and strengthen an existing plan.
Turn Airflow Improvement Proposals into practical guides checked against current code, or proposed user stories for design review before implementation. Organize use cases, distinguish verified examples from speculative code, and capture specific design questions.
Use LitGPT to explore language model implementations and train models on custom data. Covers pretrained model loading, LoRA fine-tuning that updates a small set of parameters, pretraining, and preparing trained models for deployment.
Turn a feature idea into a detailed implementation plan through research, interviews, and reviews by Gemini and Codex. Produce self-contained work sections with dependencies and acceptance criteria, plus files for supported automated implementation workflows.
Turn Figma screens and components into application code using design specifications, screenshots, and supplied assets. Reuse existing project components and shared style values, then check layout, typography, responsive behavior, and accessibility against the design.
Review an OpenSpec implementation against its specifications, tasks, and design decisions. The skill checks for missing work, uncovered scenarios, and inconsistencies, then produces a prioritized report with concrete recommendations and code references where available.
Turn a plan, specification, or concrete development request into implemented changes with local verification. Run it independently for a review and delivery handoff, or return implementation results to a calling workflow.
Use LitGPT to explore language model implementations and train models on custom data. Covers pretrained model loading, LoRA fine-tuning that updates a small set of parameters, pretraining, and preparing trained models for deployment.
Fetch design structure, screenshots, variables, and assets from Figma through MCP, a connection between the agent and Figma. Use these references to guide code implementation within an existing project and troubleshoot connection setup.