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概要と使いどころ
Manage service components and approval workflows in the NV oOS Pro Toolkit. Covers service component registration, dependency tracking, approval request lifecycle, and workflow approval gates. Use when registering service components, tracking service dependencies, managing approval requests, or configuring workflow approval nodes.
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。
Design and interpret TypeSafe Jev decision requests in NV oOS — typed choice/score/noul questions, batching, confidence thresholds, composite scoring, and guardrails. Use when classifying, routing, scoring, or safety-screening content with the typesafe_decide or typesafe_guardrail tools.
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。
Refresh Claude Ads platform, API, policy, regulation, benchmark, issue, pull-request, fork, and repository evidence. Use for ads research refresh, expired refresh_due dates, stale API or platform claims, reverify-or-demote decisions, release-current claim validation, ecosystem review, current platform changes, or updating paid-media knowledge. When tools or sources are unavailable, still demote the stale claim for the current run and block dependent release-current assertions before requesting access.
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。
リファクタリングを「更新されたチームの理解と、コードが表現する過去の理解の差分同期」と捉え、今回得た新知識（要求・ドメイン知識・制約）が naming と responsibility へ反映されているか、boundary が現在の understanding を表現しているか、diff の削除行やコメントに現れる過去の design history と constraint を失っていないかを diff-time で確認する。Knowledge Delta の signal は diff（追加/削除された hunk・コメント・ADR 参照）を一次情報とし、PR 本文が供給されるときは補助に用い、不確実なら question に留める。ドメイン用語の一貫性は ubiquitous-language-naming、集約/コンテキスト境界の設計判断は bounded-context-language、投機的抽象化・caller special-case は altitude-generalization、スコープ逸脱/前提破壊は fix-scope-integrity、振る舞い変更と構造変更の分離は behavior-structure-separation、完了主張の反証は refactor-claim-audit へ委譲する
Ensure design docs explicitly capture risks, assumptions, and open questions with owners, deadlines, and mitigation plans.
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。
指摘対応の反復（レビューコメント→修正→再レビュー）で、個別には正しい修正の蓄積が当初スコープを逸脱した（scope creep）、または成立済みの前提（"動いていた"状態）を破壊した（premise break）連鎖を diff-time で検出する。技術的正しさとスコープ整合性を別軸で評価し、report-only で finding/question のみ出力する。1コメント単位のトリアージ・構造変更後の caller 残骸・plan 前提解消は隣接 skill へ委譲する
リファクタリング（構造変更）と機能変更（behavior change）が同一 diff に混在していないかを識別し、structural change に対する external behavior preservation の証拠（テスト・型・静的解析）が揃っているかを diff-time で確認する。証拠不足のときは Characterization Test 追加を促すか question とする。DTO/公開 API の破壊的変更検出は api-compatibility、完了主張の反証や抽出リファクタの性能特性退行は refactor-claim-audit、新知識の命名・責務・境界への反映は knowledge-to-code-alignment、投機的抽象化・スコープ逸脱は altitude-generalization / fix-scope-integrity へ委譲する
Create an HTTP Ingest (webhook) capture to receive data via HTTP POST requests. Use when setting up webhooks from GitHub, Shopify, Stripe, or any JSON source. Use when user says "set up webhook capture", "HTTP ingest to Estuary", "receive POST requests to Estuary", or "webhook capture".
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。
PRをレビューしてGitHubにコメントを投稿する。reviewerエージェントが検証し、結果に応じてapprove/request-changesを実行する
在授权渗透测试中系统性挖掘 HTTP 请求走私（HTTP Request Smuggling / desync）。当目标前面有反向代理/CDN/负载均衡（前端）转发给后端应用，且怀疑前后端对 Content-Length 与 Transfer-Encoding、畸形头、chunked trailer 的解析不一致时使用——典型场景：想毒化后端 socket 劫持他人请求、批量窃取会话 Cookie/令牌、缓存投毒、绕过前端访问控制。适用目标类型 Web / REST API（有分层代理）。触发场景包括用户说"测下有没有 HTTP 走私/desync""这个 CDN 后端解析一致吗""能不能毒 socket 偷别人 cookie""CL.TE / TE.CL 打一下"。输出：带 desync 时序证据与原始报文的 finding 报告（含 killed 记录）。
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 pull request from the current branch for claude-statusline, into the right base for this repo's two-tier flow — feature branches (`dev-<feature>`) target `dev`, and `dev` itself targets `master` as a release PR. Analyzes the new commits, drafts a PR title and a Summary/Test-plan body matching this repo's existing PR style, previews it for approval, then creates it via the `gh` CLI. Use whenever the user says "pr", "pull request", "open a pr", "create pr", "ship it", "merge into dev", "merge into master", "raise a pr", or anything about getting the current branch merged — even if they don't say the word "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。
Implement distributed tracing with Jaeger and Tempo to track requests across microservices and identify performance bottlenecks. Use when debugging microservices, analyzing request flows, or implementing observability for distributed systems.
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。
place_blocks ツールの引数形式、PlaceRequest、フェーズ配列、connects/attaches の使い方。ブロック配置前に必ず読む。
CLI版 mc-cli place-blocks コマンドの引数形式、PlaceRequest、フェーズ配列、connects/attaches の使い方。ブロック配置前に必ず読む。
Act as FriendlyBet's CEO and primary front door for every FriendlyBet request through automatic company preflight. Own end-to-end routing, planning, execution coordination, department orchestration, decision-rights enforcement, quality gates, board-style reporting, and escalation only for strategic, legal, brand, cost, risk, or taste decisions. Use by default in FriendlyBet threads, with full department planning for broad, ambiguous, strategic, cross-functional, or outcome-driven requests such as SEO, new features, multi-sport expansion, product direction, release execution, company operations, or agent coordination.
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。
Zod 4 — TypeScript-first schema validation with static type inference. Use when writing Zod schemas, validating data, defining types with Zod, parsing input, creating form validation schemas, defining API request/response schemas, working with z.object, z.string, z.number, z.enum, z.array, z.union, z.discriminatedUnion, z.file, z.jwt, z.email, z.uuid, z.url, z.codec, z.toJSONSchema, z.fromJSONSchema, z.int, z.stringbool, z.templateLiteral, z.record, z.partialRecord, or any other Zod API. Also use when migrating from Zod 3 to Zod 4, or when the user's package.json shows zod@^4. CRITICAL: Always use Zod 4 APIs. Never use deprecated Zod 3 patterns unless user explicitly requests Zod 3 compatibility.
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。
Startup skill router: maps any incoming request to the correct skill using Quick Lookup table and _manifest.json. Loaded automatically at session start. Triggers on: every new request — this is the dispatch layer, not a user-facing skill. NOT for: executing tasks directly — always routes to a domain-specific 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。
Multi-source research synthesizer. Takes a question, runs 3-5 parallel web searches with varied phrasings, deduplicates, and returns a cited, concise answer. For Hebrew questions, searches in both Hebrew and English. Output is always under ~400 words.
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。
Use when working with Aws Codecommit — aWS CodeCommit repository management and analysis. Covers repository inventory, branch details, pull request status, commit history, approval rules, and trigger configurations. Use when inspecting repositories, reviewing pull requests, auditing branch policies, or analyzing commit activity.
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。
Plan, execute, and document validation, verification, and transfer of analytical procedures under the governing framework - ICH Q2(R2) and Q14, USP <1220>/<1225>/<1226>, ICH M10 bioanalytical, CLSI EP, or ISO/IEC 17025. Use for HPLC, LC-MS/MS, GC, CE, ICP-MS, dissolution, qNMR, qPCR, NIR, and ligand binding or cell-based assays whenever the question is whether a procedure is fit for its intended purpose. Triggers include "method validation", "analytical method validation", "AMV", "validation protocol", "acceptance criteria", "linearity", "reportable range", "accuracy and precision", "repeatability", "intermediate precision", "recovery", "LOD", "LOQ", "detection limit", "quantitation limit", "specificity", "robustness", "method transfer", "method comparison", "Deming", "Passing-Bablok", "Bland-Altman", "equivalence testing", "OOS investigation", "ICH Q2", "Q2(R2)", "Q14", "USP 1225", "ICH M10", "incurred sample reanalysis", "ISR", "CLSI EP", and any request to show that an assay works.
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。
Dispatch code-reviewer subagent to review implementation against plan or requirements before proceeding
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。
Write, configure, and deploy Netlify Edge Functions (Deno runtime at the network edge) in TypeScript/JavaScript. Use when adding request/response manipulation at the edge — auth middleware, geolocation redirects, A/B testing and personalization, content localization, redirects/rewrites, SSR at the edge, or transforming responses — or when configuring path routing, response caching, or edge error handling. Triggers on tasks like "add auth middleware", "geo-based redirect", "A/B testing at the edge", "rewrite requests", or editing files in netlify/edge-functions.
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。
Plan and coordinate the deployment of a model to Amazon SageMaker AI. Use this skill whenever the user wants to deploy, host, serve, or expose a model on SageMaker or AWS — including phrases like "deploy a model", "host this LLM on AWS", "serve this embedding model", "deploy a reranker", "deploy a text-to-image / diffusion model", "host this for async inference", "create an endpoint", "serve my fine-tuned model", or any request that involves making a model available for inference on AWS. Use this even when the user is vague (e.g. "I just want to get this running on AWS, you figure it out"). Works for text-generation LLMs, embedding models, rerankers, classifiers, text-to-image / diffusion models — picks the right serving stack and chooses between real-time and async inference. This is the entry-point skill for SageMaker deployment work — it asks clarifying questions, picks a deployment pathway, and coordinates the other deployment skills.
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。
Use only when the user explicitly requests strict code-cell-only output for a Jupyter or undergraduate data-science task, or when an ITX2007 assignment requires that format. Do not activate for ordinary data analysis or explanation requests.
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。