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概要と使いどころ
This skill recommends obtaining a postoperative pituitary MRI within 1–3 months after successful transsphenoidal surgery (TSS) to establish a new baseline for future recurrence assessment. Use when a Cushing’s syndrome patient has achieved biochemical remission post‑TSS and is entering routine follow‑up.
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This skill recommends measuring late-night salivary or serum cortisol to screen for Cushing's disease recurrence in patients with eucortisolism after transsphenoidal surgery, including cases where eucortisolism was established by medical treatment prior to surgery. Use when postoperative follow-up shows eucortisolism (normal morning cortisol/UFC) but concern for recurrence exists.
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Determines follow‑up interval for patients with primary adrenal insufficiency (PAI) based on age: annual visits for adults and children, and every 3–4 months for infants. Triggered when establishing routine endocrine care after PAI diagnosis or during stable management.
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Recommends measurement of plasma ACTH to establish primary adrenal insufficiency (PAI) diagnosis in patients with confirmed cortisol deficiency; a plasma ACTH concentration ≥2-fold the upper limit of the reference range supports PAI. Use when evaluating plasma ACTH in a patient with low morning cortisol or abnormal corticotropin stimulation test.
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Derive an execution roadmap from a project's vision/spec docs by first principles, then diff that fresh derivation against the existing roadmap to prove the task ORDER is correct. Use this whenever the user wants to review, validate, re-derive, or sanity-check an execution roadmap or delivery plan; asks whether the tasks/epics are "in the right order"; suspects a task is scheduled before its prerequisite (a producer-after-consumer / dependency-inversion error like "OpenAPI after the web client that consumes it", OR a cross-cutting inherited default like observability/auth/tenancy scheduled after the feature work that inherits it — a seam-after-consumer error); wants to find missing tasks, circular dependencies, or over-fragmented epics; or wants to compact a plan to raise velocity. Also trigger on "review the roadmap", "re-derive the plan from the spec", "is this the right build order", "check the dependency graph of our epics", "which task should come first". It reads the vision + spec corpus, decomposes actors → use-cases → modules → epics → typed tasks, identifies cross-cutting inherited-default seams, builds a real dependency graph with hard + soft (seam) edges (deterministic helper), breaks cycles, topologically orders, compacts, and emits a derived roadmap PLUS a delta report against the current one — it never blindly overwrites a hand-crafted roadmap.
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Propose the next dependency-ready sprint from the ALREADY-DECOMPOSED roadmap — standup's active sibling. Reads docs/roadmap-execution-plan.md + the memory backlog, computes per-task readiness from the roadmap's machine-readable status, orders with roadmap-planner's graph engine, and emits a proposed task-set (sprint-plan manifest shape) with per-feature done-criteria, excluding unready tasks and naming their unmet prerequisite. PROPOSES ONLY — the human confirms/edits before /triage routes it (typically to the `power` track). Distinct from `sprint-plan`, which decomposes a fresh vision.
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npm 릴리스 운영. release 브랜치 선택 커밋 반영, 검증, publish, tag, GitHub Release, main 동기화 진행
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Take a markdown file of raw material and shape it into an article through a conversational session — drafting candidate openings, growing the piece paragraph by paragraph, arguing about format (lists, tables, callouts, quotes) at each step. Use when the user has a pile of notes, fragments, or a rough draft and wants help turning it into something publishable.
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Turn the current conversation context into a PRD and publish it to the project issue tracker. Use when user wants to create a PRD from the current context.
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Use when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative agreement or blind implementation
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Use when starting any conversation - establishes how to find and use skills, requiring Skill tool invocation before ANY response including clarifying questions
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Records decisions and documentation. Use when making architectural decisions, changing public APIs, shipping features, or when you need to record context that future engineers and agents will need to understand the codebase.
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Automates CI/CD pipeline setup. Use when setting up or modifying build and deployment pipelines. Use when you need to automate quality gates, configure test runners in CI, or establish deployment strategies.
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Build event-driven applications with Azure Event Grid SDK for Java. Use when publishing events, implementing pub/sub patterns, or integrating with Azure services via events.
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Azure Event Grid SDK for .NET. Client library for publishing and consuming events with Azure Event Grid. Use for event-driven architectures, pub/sub messaging, CloudEvents, and EventGridEvents.
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Azure Event Grid SDK for Python. Use for publishing events, handling CloudEvents, and event-driven architectures.
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Comprehensive REST API design review with automated linting, breaking-change detection, and design scorecards. Catches inconsistent conventions, missing versioning, and design smells before APIs ship. Use when reviewing a PR that adds or changes API endpoints, auditing an existing API for v2 migration, or establishing API standards for a team.
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/cs:ai-act-readiness <system> — EU AI Act 6-question forcing interrogation. Use during AI-system intake, before EU deployment, or during annual compliance refresh as Article 113 obligations phase in (2025-02-02 / 2025-08-02 / 2026-08-02 / 2027-08-02).
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Adversarial code review that breaks the self-review monoculture. Use when you want a genuinely critical review of recent changes, before merging a PR, or when you suspect Claude is being too agreeable about code quality. Forces perspective shifts through hostile reviewer personas that catch blind spots the author's mental model shares with the reviewer.
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。
Local-only regression / benchmark skill for ui-clone-skills maintainers. Drives the standard ui-reverse-engineering pipeline against the canonical reference site (https://realfood.gov) and records AE/SSIM, iteration count, gate fail counts, and outcome to benchmark/history.csv so prompt / sub-doc / model-version drift surfaces as a trend. Trigger phrases: "run benchmark" / "regression benchmark" / "benchmark clone". The Makefile no longer has a `benchmark` target — setup is inline bash in this skill (Step 1 below). Internal: NOT registered in `.claude-plugin/plugin.json` `skills`. Not part of the public 3-skill marketplace surface. Maintainer tooling only.
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Use when Amazon Ads optimization analysis, recommendations, approval packets, demos, recordings, or public artifacts must preserve exact source KPIs while masking account/profile/project names, products, ASINs, SKUs, campaigns, ad groups, keywords, search terms, targets, placements, filenames, URLs, and source-derived identifiers. Produces masked approval packets only; it must not directly mutate Amazon Ads.
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Core skill activation protocol - establishes mandatory workflows for finding and applying skills before any task
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Discover prospect companies from a structured OpenClaw search brief, including public search and user-authorized data sources, then output a conservative candidate list ready for lead screening.
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Find the first batch of foreign-trade prospect companies from public web, LinkedIn, and user-authorized data sources such as customs exports, trade show lists, association directories, CRM/Excel files, or historical customer data, then output a conservative, structured candidate list ready for lead screening.
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。