8K skills · sorted by relevance
Convert a Notion specification into a linked implementation plan and manageable tasks. Extract requirements and acceptance criteria, record uncertainties, and keep task statuses, checklists, blockers, and milestone updates aligned as the work progresses.
Create the OpenSpec documents needed to begin implementing a feature or fix. Follow the workflow's dependency order and templates, using completed documents as context until all prerequisites for implementation are ready.
Implement a planned game development task by gathering its specifications and design decisions, then assigning the right programming specialist. Coordinate source changes, tests where required, visual evidence, and session state for subsequent review and closure.
Implement, fix, refactor, or remove repository code through a defined workflow. It connects each change to an acceptance criterion, checks effects on existing behavior, and guides focused testing, change review, and verification.
Implement Verdaccio fixes, features, or refactoring after checking whether existing settings or plugins already solve the problem. Place changes in the responsible component, reuse helpers, add tests and release notes, and validate affected packages.
Convert a Notion specification into a linked implementation plan and manageable tasks. Extract requirements and acceptance criteria, record uncertainties, and keep task statuses, checklists, blockers, and milestone updates aligned as the work progresses.
Build web application features across the interface, API, and database, with authentication, input checks, and safe data handling. The skill guides technical design, implementation, error handling, and component testing in one workflow.
Generates cryptographic test vectors, inputs with expected outcomes, by deliberately changing implementation code and finding changes existing tests miss. Verifies new vectors across independent implementations and compares detection rates before and after adding them.
Turn Notion product requirements and feature specifications into linked implementation plans and manageable tasks. Extract requirements, flag ambiguities, and keep task status, milestones, blockers, and decisions aligned as work progresses.
Guide code changes in iPolloWork by reusing existing implementations, limiting new files and dependencies, and keeping responsibilities clear. Review runtime costs, run focused checks, and audit the final changes for duplication and maintainability issues.
Turn a Figma design into code that fits an existing project. Reuse its components and shared style values, follow designer notes and component mappings, and adapt Figma's reference output to the project's framework and conventions.
Create the OpenSpec documents needed to begin implementing a feature or fix. Follow the workflow's dependency order and templates, using completed documents as context until all prerequisites for implementation are ready.
AI DevKit · Implementation phase guidance for executing feature plans and checking implementation against design. Use when the user wants to implement planned tasks, update implementation docs, verify code matches design, or run dev-lifecycle phases 5 and 7.
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Load code-style and task-specific skills, make the change described by the current context, then run post-implementation QA. Use for ad-hoc changes when no plan file or improvements backlog governs the work, and when the user asks to "just implement", "implement directly", "implement without a plan", or "apply the change".
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Break a trusted implementation plan (or other provided context) into independently-grabbable, atomic work items, written to a single work-items.md file. Use when the user wants to convert a plan into work items, create implementation tickets or tasks, divide a plan into work units, or break the plan down into grabbable pieces. Do not use when there is no implementation plan yet or the plan is not yet trusted — use plan-implementation to produce the plan or iterative-plan-review to harden it first. Does not sequence work into demoable delivery phases — use plan-a-phased-build for that. Does not write code — use tdd to implement a work item.
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Implement a single Flutter task following this repository's Riverpod, Freezed, AutoRoute, DTO/entity, codegen, and verification conventions. Reads the task definition, PRD, and tech spec, then executes the implementation. When invoked standalone, verifies the change; when invoked by implement-tasks-sequence, writes code only and leaves verification to start-job/build-verify. Use when the user says "implement task X", "work on task X", or wants to execute a specific task from the task list.
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Own goal-first engineering outcomes: investigate, find root cause, design, plan, then delegate implementation unit-by-unit to cursor-implementation-loop, this plugin's kernel skill, with verification and honest reporting. Use to fix, build, or own an outcome end to end; investigate-and-fix; "make X work"; or plan-then-execute in one request. A request with an approved plan or equivalently precise spec that needs nothing beyond implementation belongs directly to cursor-implementation-loop. Requires this plugin's cursor-implementation-loop skill; they ship together.
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Delegate implementation to Codex or to a sandboxed Claude Code (`claude -p`), have a model from the other vendor review the diff, send it back to iterate, gate on the full test suite, and ship it as a PR. Use this whenever the user wants Codex or a sandboxed Claude to write code, mentions handing off / delegating implementation to one of those backends, asks for a cross-vendor review of delegated code, asks to work through a plan or spec unit-by-unit with an implementation backend doing the coding, or wants a review-and-merge loop wrapped around delegated output — and also when resuming such a loop ("keep going", "next unit", "继续下一个"). It encodes constraints that are expensive to rediscover: the implementer runs in the real environment behind backend-specific git and publication boundaries, must not be pointed at a full test suite by default, and its self-report is a claim rather than evidence. This loop expects an approved plan or an equivalently precise spec; settle an unsolved high-level goal into a plan first, using the engineering-mode skill when it is installed.
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Own goal-first engineering outcomes: investigate, find root cause, design, plan, then delegate implementation unit-by-unit to implementation-loop with verification and honest reporting. Use to fix, build, or own an outcome end to end; investigate-and-fix; "make X work"; or plan-then-execute in one request. A request with an approved plan or equivalently precise spec that needs nothing beyond implementation belongs directly to implementation-loop. Requires implementation-loop and an authenticated backend CLI to execute.
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Implement a ready rolling-wave slice without locking it down with broad tests yet. Use when the user explicitly wants to code the current docs/rolling-wave/{project}/slices/NNN-slug.md slice, mark it in progress while working, implement small or cohesive work in the main context by default, use one to three gpt-5.6-terra workers only for genuine parallel chunks or large discovery/mechanical work where delegation pays for its handoff cost, pause or hand off chunks marked human-fit when appropriate, record implementation notes and final-test backlog, preserve the original slice contract, and mark completed implementation ready for review.
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Implement and finalize one ready rolling-wave slice in one invocation while preserving the lifecycle boundary between implementation and independent review. Use when the user wants a slice delivered end to end without manually invoking implement-slice and finalize-slice, wants main-local implementation by default with workers only when delegation pays, followed by mandatory fresh-context finalization, or says deliver, implement and finalize, or take the slice through review.
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Implements one issue in its own git worktree (agent/issue-N): smallest correct change, self-check, commit, JSON report. Use when launched with AGENT_FLOW_ROLE=implementer or asked to implement a specific issue in a worktree.
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Implementa e treina LLMs usando LitGPT da Lightning AI com 20+ arquiteturas pré-treinadas (Llama, Gemma, Phi, Qwen, Mistral). Use quando precisar de implementações limpas de modelos, entendimento educacional de arquiteturas ou fine-tuning de produção com LoRA/QLoRA. Implementações em arquivo único, sem camadas de abstração.
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ISTQB/JSTQB のテスト実装（test implementation）活動を支援するスキル。test-design が導出したテストケースを、実行できる形に具体化する。自動テストなら実行手順（テストコード・テストデータ・テストダブル）をコンパイル/構文レベルの動作確認まで、手動テストなら手順書・テストデータ・環境準備手順を作る。「テストケースを実装して」「テストコードに落として」「テスト手順書を作って」「テストデータ・モックを用意して」と依頼されたときに使う。テスト対象の検証としての実行（結果の解釈・欠陥候補整理）は test-execute の担当でここではしない。単発のテスト作成依頼（単にユニットテストを書きたいだけ）は対象外。/test-implement <テスト対象名> で明示的に呼び出されたときのみ使用する。
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