425 件 ・ 関連度順
概要と使いどころ
When the user says 'refactor this', 'rename class', or 'move method'. Safely refactors code in any language — finds all callers, updates downstream dependencies, verifies via quality 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。
[Code Quality] Use to validate a spec artifact's decisions with the user across three contexts — a freshly-authored Feature Spec (idea-to-spec), an existing canonical spec before PBI decomposition (spec-to-pbi), or a refined idea + §8 test-specs (idea-to-pbi deep mode). Detects the context, walks every applicable validation category, and runs an exhaustive but budget-bounded blocking clarification gate so every non-obvious or conflicting decision is confirmed before the artifact drives downstream work.
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。
Define legal scope, rules of engagement, and authorization artifacts for downstream pentest execution.
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。
Collect project brief and stack choices, then output canonical project-config.json for downstream web-builder 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。
GStack spec method for turning fuzzy intent into an executable spec with goals, non-goals, acceptance criteria, risks, and downstream role boundaries.
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。
Discipline for repairing a false claim once it has propagated: select what depends on it, produce a replacement, and accept with an expiring verdict. Trigger when: - A claim, citation, premise, or documented fact is found wrong and its downstream consequences must be traced and fixed. - A refutation, a failed re-run, a retracted external source, or a human correction lands against something already closed or already promoted. - Prompt contains: /remediation, remediation, retraction, false claim, propagated error, scrub, correction propagation, born-false, became-false, currency verdict, impeachment queue.
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。
Efficiently extract and convert the contents of any local file—such as PDF, DOCX, DOC, ODT, RTF, XLSX, XLS, or HTML—into clean, well-formatted markdown saved to disk. Use this skill whenever the user requests to parse, read, or extract information from a file on their computer, including phrases like “parse this PDF”, “convert this document”, “read this file”, “extract text from”, or when a local file path (not a URL) is provided. This skill offers advanced options like generating AI-powered summaries and answering questions based on the file's content. Prefer this tool over `scrape` when handling local files to deliver precise, structured outputs for downstream tasks.
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。
Set up notebook-connector configuration for Exasol AI workflows through the Secrets Python API. Covers secure config store (`scs`) creation, the `AILabConfig` and `StorageBackend` key sources, backend-specific config values such as `db_host_name`, `db_schema`, `storage_backend`, and `huggingface_token`, Python validation, and handoff to downstream notebook-connector 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。
Translate a fuzzy analytical question into a rigorous investigation plan. Interrogates the ask, grounds the plan in the available data dictionary, applies analytical best practices, and produces a structured brief of query specifications for a downstream query-writing skill. Plans, does not write SQL. Use when: "why did X drop", "is there a relationship between A and B", "who are our highest-value customers", "what's driving the change in Y", "investigate this trend", "design an analysis for", "scope this analytical question". (narrative-common)
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。
Analyze a local codebase and infer the architecture it is actually using, including repo kind, best-fit dominant architecture, directly evidenced coexisting patterns, major subsystem exceptions, confidence, docs-vs-code drift, and repo-fit hints for downstream agents. Use when prompts ask what architecture a repo uses, whether it is really hexagonal or just layered, what subtle patterns shape a repo or slice, how a target slice fits a hybrid monorepo, whether documented architecture matches implementation, or when `/tw-tk` needs a repo-dialect preflight before making a minimal change.
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。
Load for Blazor BFF server work involving YARP proxy routes, cookie sessions, access-token forwarding/refresh, downstream API calls, BFF handlers, or browser-to-API auth failures; not for client component rendering or API JWT validation alone.
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。
Author a completed-spec fixture — a seeded intent graph plus a believable four-phase interview transcript — for a brunch feature, so it can feed any downstream tooling that consumes a completed spec or dogfood the UI. Use when you need a real completed specification in .brunch/brunch.db for testing or demo: pick a feature from memory/SPEC.md (or a free description), choose a stress profile (coverage|clean), and produce a registered scenario seed + an interview-questions doc that match exactly.
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。
Finds high-value SEO and GEO keywords using web search, AI analysis, and optionally paid tools like Ahrefs or Semrush. Produces a validated keywords.csv file with a fixed schema for downstream pipeline consumption.
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 a user provides a GitHub URL and the planner needs to converge that repo plus the user's goal into a concrete project blueprint for later execution. This skill handles GitHub-input project intake, Phase 1 intent convergence, and downstream project handoff structure. It does not generate teaching material packages.
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。
How to read submitted JetFormBuilder form data from a custom action, transform it (including %macro% replacement of admin-typed templates), call an external HTTP API, write the response back into the form context for downstream actions to use, and dispatch JFB events based on the API outcome. Use when building a custom action that integrates with a third-party service (LLM call, webhook, CRM, payment processor, geolocation lookup) and needs the action to behave as a node in a data-flow graph rather than a one-shot leaf. Triggers on mentions of "jet_fb_context", "update_request", "has_field", "get_value", "wp_remote_post" with form data, "macro replacement", or "API call from action".
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。
Build or update the shared product-marketing context: product, audience, positioning, competitors, jobs-to-be-done, objections, customer language, proof and goals. Use before downstream execution when context is missing.
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。
Find missing tests for critical paths, edge cases, and failure handling in changed code.
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。
変更差分から重要なテスト観点と欠落を洗い出し、優先度付きでテストケース案を提示する
Ensure tests use clear naming and cover edge cases with proper describe/it structure.
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。
Check whether changed code paths have corresponding tests and suggest minimal coverage.
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。
テストは存在するがアサーションが実質何も検証しておらず、実装が壊れても落ちない（常に PASS する）構造を diff-time で検出する。Check 1 missing assertion（テスト本体にアサーションが無い）、Check 2 tautological assertion（定数同士・入力自身・mock の戻り値自身を assert し SUT に依存しない）、Check 3 nonexistent expected literal（assertDontSee / assertNotContains 等の期待文字列が対象ファイルに実在しない）、Check 4 stale expected value（同一 diff で対象の出力が変わったのに期待値が据え置き）、Check 5 unscoped expectation（汎用的な属性・クラスを応答全体に対して assert し対象要素にスコープされていない）、Check 6 swallowed failure（例外の握り潰しや到達しない位置のアサーションで判定が成立しない）、の 6 Check を対象とする report-only。テストの有無は test-existence、未テスト経路の量は coverage-gap、非決定性は flaky-test、命名は test-naming、JS/TS の un-awaited resolves / rejects は vitest-mock-isolation、tdd-ledger artifact ベースの RED/GREEN 検証は plangate-tdd-evidence、.only / .skip / xit / @ts-ignore と空の catch は heuristic-review.mjs の決定論検出器へ委譲する
Reviews GitHub Actions workflow diffs for script injection of untrusted input, pull_request_target with untrusted checkout, over-broad GITHUB_TOKEN permissions, and unpinned third-party actions.
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。
Detects patterns that make tests flaky and proposes stabilization steps.
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 before writing logic: choosing core types and data structures, sequencing scaffold-vs-feature work, asking what concurrent actors share. Get the data structures right so downstream code becomes obvious.
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。