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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.
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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.
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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.
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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'.
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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).
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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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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".
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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.
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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.
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检查新旧测试实际保护的行为和可检测的缺陷，审视重复检查及对实现细节的依赖。删除前整理依据，保留必要验证，并清理仅供测试使用的代码。
将规格或需求整理成实施计划，明确要修改的文件、函数定义、测试和验证步骤。在编写代码前拆分工作，形成可交给其他人员或代理执行的任务。
为功能开发准备独立工作区，先检查是否已隔离，再使用环境内置功能或 git worktree 创建，并完成依赖准备和修改前的测试。
在仓库文件中管理开发计划，将大目标拆成小任务并分配到迭代，记录实现、审查和合并确认的进展，无需外部项目管理工具，还可检查任务文件与汇总表的不一致。
将尚未实现的新功能从调研、规划推进到测试先行的开发、审查和提交。各阶段交由对应的ECC智能体负责，并在计划批准和提交前暂停确认。
在实施前通过有针对性的追问，明确计划的目标、约束、技术选择和异常应对。按决策依赖关系逐轮提问，整理已定事项与未解决问题，统一理解。
将实施计划中的任务分别交给上下文独立的子智能体，先检查是否符合规格，再审查代码质量。发现问题后反复修正和复查，最后检查各部分的集成情况。
通过Hermes终端将代码实现、缺陷修复和PR审查交给Blackbox AI，比较并选择多个模型的结果，监控长任务，并从保存的检查点继续工作。
在编写代码前，从技术角度审查实施计划，检查系统结构、数据流、边界情况、测试覆盖和性能。通过讨论各项问题与建议方案，确定后续实施方向。
检查重复、缺乏实质验证或依赖内部实现的测试，逐项确认删除依据与保留的替代测试，在保留问题复发检测能力的前提下，合并、修复或删除测试。
Investigate a Homecore capability by tracing relevant source files, tests, and accepted architecture decisions. Check documented status and limitations before proposing code, while keeping implementation presence separate from deployment compatibility or claims of Home Assistant parity.
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Organize new features, complex implementations, and architecture changes into the SPARC stages: specification, pseudocode, architecture, refinement, and completion. Define requirements and acceptance criteria, consult existing patterns, and record lessons for future work.
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Prepare the OpenSpec documents needed to start implementation in one pass. It examines the project and creates required proposals, specifications, designs, and tasks in dependency order, following the project's configured workflow.
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Turn a feature idea or fix request into an OpenSpec implementation plan. The skill examines the project and prepares the required proposal, specification changes, design, and tasks for review, without changing project code.
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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.
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