「implementation」の検索結果

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.

日本語の概要は準備中です。原文の説明を表示しています。

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.

日本語の概要は準備中です。原文の説明を表示しています。

Review the implementation source code of MCP (Model Context Protocol) servers, clients, and tool handlers against a security baseline — authentication, sessions, rate limiting, input-schema validation, official-SDK usage, RCE vectors, and the OWASP MCP Top 10 — producing a report with file/line evidence. Use this skill when: - Reviewing an MCP server implementation for security before release - Checking a server against the baseline controls (MCP-01 to MCP-05) and the OWASP MCP Top 10 - Auditing tools for RCE vectors (command/code injection, unsafe deserialization, path traversal, SSTI, dependency hijacking, SSRF) - Verifying auth, session, rate-limiting, and input-validation controls on a network-exposed server - Reviewing MCP client code that handles untrusted server responses and session IDs - Requests like "review this MCP server for security" or "is my MCP server implementation secure?"

日本語の概要は準備中です。原文の説明を表示しています。

Scores how completely an implementation fulfills a PRD/spec, case by case, and produces a single comparable final grade. Invoke only when explicitly named (e.g. run spec-driven-eval); do not auto-trigger. Use when benchmarking spec-driven implementations, grading acceptance criteria, evaluating whether a feature was 100% implemented, comparing multiple implementations of the same PRD, or auditing implementation and test coverage (unit and e2e) against product requirements. Do NOT use for planning or building features (use tlc-spec-driven), writing PRDs, or general code review unrelated to a spec.

日本語の概要は準備中です。原文の説明を表示しています。

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.

日本語の概要は準備中です。原文の説明を表示しています。

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.

日本語の概要は準備中です。原文の説明を表示しています。

Authentication & Authorization Implementation Patterns workflow skill. Use this skill when the user needs Build secure, scalable authentication and authorization systems using industry-standard patterns and modern best practices and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

日本語の概要は準備中です。原文の説明を表示しています。

Authentication & Authorization Implementation Patterns workflow skill. Use this skill when the user needs Build secure, scalable authentication and authorization systems using industry-standard patterns and modern best practices and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

日本語の概要は準備中です。原文の説明を表示しています。

Study a merged or shipped tdmcp implementation and extract reusable learnings: code improvements, runtime/UX lessons, test gaps, docs updates, roadmap items, and harness changes. Use when the user asks to learn from a completed feature/project/PR/build, analyze what can be improved from an implementation, or turn a real installation experience into actionable tdmcp improvements. This is a post-implementation learning harness; it does not replace tdmcp-pipeline for building or tdmcp-quality-audit for broad repo audits.

日本語の概要は準備中です。原文の説明を表示しています。

Post-implementation review orchestrator. Launches 5 parallel background sub-agents: Oracle (goal/constraint verification), Oracle (code quality), Oracle (security), unspecified-high (hands-on QA execution), unspecified-high (context mining from GitHub/git/Slack/Notion). All must pass for review to pass. MUST USE after completing any significant implementation work. Triggers: 'review work', 'review my work', 'review changes', 'QA my work', 'verify implementation', 'check my work', 'validate changes', 'post-implementation review'.

日本語の概要は準備中です。原文の説明を表示しています。

Delegate implementation to Codex, grok, or cursor-agent, then 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, the grok 后端, or cursor-agent to write code, mentions handing off / delegating implementation to one of those backends, 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.

日本語の概要は準備中です。原文の説明を表示しています。

Delegate implementation work to a dedicated implementer subagent, then review its diff, send it back to iterate, gate on the full test suite, and ship it as a PR. Use this whenever the user wants a separate model to write code, mentions handing off / delegating implementation, asks to work through a plan or spec unit-by-unit with a subagent 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 self-reports success, must not run the full test suite by default, must not touch git, and its report is a claim rather than evidence. Cursor port of implementation-loop. This loop expects an approved plan or an equivalently precise spec; settle an unsolved high-level goal into a plan first, using the cursor-engineering-mode skill (it ships in this same plugin).

日本語の概要は準備中です。原文の説明を表示しています。

組織変革管理の専門コンサルタントスキル。システム導入、組織変革、DXプロジェクトにおける変革管理を支援。 ADKAR、Kotter 8-Stepフレームワークに基づき、ステークホルダー影響度分析、コミュニケーション計画、抵抗管理戦略を提供。 Use when managing organizational change, system implementations, digital transformation projects, or improving user adoption rates. Triggers: "change management", "organizational change", "system implementation", "user adoption", "change strategy", "stakeholder engagement".

Study a merged or shipped tdmcp implementation and extract reusable learnings: code improvements, runtime/UX lessons, test gaps, docs updates, roadmap items, and harness changes. Use when the user asks to learn from a completed feature/project/PR/build, analyze what can be improved from an implementation, or turn a real installation experience into actionable tdmcp improvements. This is a post-implementation learning harness; it does not replace tdmcp-pipeline for building or tdmcp-quality-audit for broad repo audits.

日本語の概要は準備中です。原文の説明を表示しています。

Create a detailed, step-by-step implementation plan for a feature or project. Load when the user asks to plan a feature, create a technical roadmap, break down a PRD into tasks, design an implementation strategy, or sequence engineering work. Also triggers on "how should we build this", "implementation plan for", "technical breakdown", "task list for", or any request to turn a high-level requirement into a concrete execution plan. Supports phased rollouts, architecture-first, and MVP-focused planning.

日本語の概要は準備中です。原文の説明を表示しています。

新規・既存テストが守る動作と不具合を確かめ、重複や実装への依存を見直すスキル。削除の根拠を整理し、必要な検証を残してテスト用コードも整理します。

• 新規テストの必要性を確かめたいとき
• 重複や実装依存のテストの点検
• テスト専用の公開コードの見直し

機能開発を別の作業領域で進めるために、既存の分離状態を確認し、環境標準の機能かgit worktreeで領域を用意。依存関係の準備と開始前のテストも行います。

• 機能開発を別の作業領域で始める
• 実装計画の開始前に環境を整える
• 作業領域が分離済みか確認する

仕様や要件を、変更するファイル・関数の定義・テスト・確認手順が分かる実装計画にまとめるスキル。コードを書く前に作業を分け、担当者へ引き継げる形に整えます。

• コードを書く前に機能実装を計画したいとき
• 要件をテスト可能なタスクに分けたいとき
• 別の担当者やエージェントに引き継ぎたいとき

まだ存在しない機能の追加を、調査・計画からテスト先行の実装、レビュー、コミットまで進めるスキル。工程を担当エージェントに分担し、計画とコミット前に承認を挟みます。

• 未実装の機能を追加したいとき
• テスト先行で新機能を実装
• 認証機能のセキュリティレビュー

Turn ambiguous or high-impact product and engineering changes into scoped, verifiable acceptance criteria before or alongside implementation. Use when a user asks to clarify a feature, define acceptance criteria, de-risk a security/data/migration/integration change, prepare implementation requirements for another agent, or make a complex request testable. Do not trigger for trivial edits, straightforward fixes, active debugging, code review, or implementation requests whose acceptance conditions are already clear unless the user explicitly invokes this skill.

日本語の概要は準備中です。原文の説明を表示しています。

Implements and trains LLMs using Lightning AI's LitGPT with 20+ pretrained architectures (Llama, Gemma, Phi, Qwen, Mistral). Use when need clean model implementations, educational understanding of architectures, or production fine-tuning with LoRA/QLoRA. Single-file implementations, no abstraction layers.

日本語の概要は準備中です。原文の説明を表示しています。

Apply Apache ShardingSphere's written coding standards when explicitly requested, or when code-implementation routes task-changed production, test, script, build, generated, or Maven POM artifacts through repository standards. Also perform a standalone read-only compliance audit of a user-specified scope. Use CODE_OF_CONDUCT.md, applicable AGENTS.md rules, Checkstyle, Spotless, and other repository-defined standards, including naming and evidence-based defensive-code rules. Do not invoke independently for an ordinary implementation already governed by code-implementation, and do not independently audit architecture, runtime ownership, caches, or lifecycle.

日本語の概要は準備中です。原文の説明を表示しています。

Implements and trains LLMs using Lightning AI's LitGPT with 20+ pretrained architectures (Llama, Gemma, Phi, Qwen, Mistral). Use when need clean model implementations, educational understanding of architectures, or production fine-tuning with LoRA/QLoRA. Single-file implementations, no abstraction layers.

日本語の概要は準備中です。原文の説明を表示しています。

Validates cryptographic implementations against Project Wycheproof's test vectors, which encode known attacks and edge cases across AES, RSA, ECDSA, ECDH, and more. Covers loading test vectors, mapping result flags onto pass and fail expectations, and reading a failure. Use when testing a crypto implementation against known attacks, checking a library against standard test vectors, or investigating why two implementations disagree on the same input.

日本語の概要は準備中です。原文の説明を表示しています。