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Review a pull request by fetching PR comments, running a comprehensive code review, evaluating findings, and dispatching to implementation. Use when the user asks to "review PR", "review pull request", "review this PR", "check PR before merging", or "full PR 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。

Create a GitHub pull request with a drafted title and description. Use when the user asks to "create a PR", "create a pull request", "open a PR", or "submit a PR".

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。

Think before typing. Root cause first, two candidate fixes, pick one, ask if still unclear, then change only the files the request needs. Edit the confidence bar and scope rules to fit the project. Use when a bug report comes in, when a previous fix did not work, or when the request is vague.

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。

This skill fetches open tasks assigned to the user from the Linear API and generates a markdown todo list file in the project root. This skill should be used when the user asks about their work items, wants to see what they need to work on, or requests to load/sync their Linear tasks. Requires Python 3.7+, requests, mdutils, and python-dotenv packages. Requires LINEAR_API_KEY in .env file.

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。

Use when the user explicitly asks for the Inngest REST API v2, raw HTTP, OpenAPI, API docs, API authentication, or an endpoint that the Inngest CLI does not expose. Covers api-docs.inngest.com, llms.txt, the OpenAPI v2 spec, Bearer authentication with API keys or signing keys, production and local base URLs, raw curl/fetch requests, request-shape discovery, pagination, secret redaction, and when to prefer the `inngest-api-cli` skill instead.

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。

Prepare a user-reviewed Arch Studio bug report or feature request for GitHub. Use when the user runs /as:studio-feedback, says "report a bug", "this skill broke", "send feedback", or requests a feature. Do not use for Claude Code's native /feedback command.

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。

Background context for invoice-system input tax credit rules (仕入税額控除) in the shinkoku tax filing plugin. Contains eligibility requirements, the 6 permanent exceptions (帳簿のみ保存の恒久特例), transitional measures for purchases from tax-exempt businesses, and storage requirements. This skill is not user-invocable — Claude loads it automatically when responding to input tax credit questions under the invoice system.

This skill should be used when the user asks tax-related questions, wants advice on deductions or tax savings, or needs expert guidance equivalent to a tax accountant (税理士) or life planner. Trigger phrases include: "税金について教えて", "控除は使える？", "確定申告の相談", "節税", "ふるさと納税の上限", "iDeCoの効果", "住宅ローン控除", "青色申告のメリット", "消費税はかかる？", "扶養に入れる？", "配偶者控除", "医療費控除", "法人成り", "経費になる？", "税率を教えて", "所得税の計算", "住民税", "社会保険料", "103万の壁", "130万の壁", "インボイス", "簡易課税", "税制改正", "開業届", "副業バレ", "白色申告", "税務調査", "特定支出控除", "予定納税", "中間納付".

Background context for housing loan tax credit (住宅ローン控除) in the shinkoku tax filing plugin. Contains eligibility requirements, credit limits, calculation rules, and interaction with furusato-nozei for the current tax year. This skill is not user-invocable — Claude loads it automatically when responding to housing loan tax credit questions or calculations.

Provides patterns for unit testing REST controllers using MockMvc and @WebMvcTest. Generates controller tests that validates request/response mapping, validation, exception handling, and HTTP status codes. Use when testing web layer endpoints in isolation for API endpoint testing, Spring MVC tests, mock HTTP requests, or controller layer unit tests.

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。

Canonical rules for finding, creating, and updating Shift GitHub issues. Use whenever the user asks to file, create, open, update, triage, or search for an issue, or when substantial work needs an issue before a pull request. Prevents duplicates and defines acceptance criteria and pull-request closure semantics.

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。

Canonical rules for preparing, opening, and updating Shift pull requests. Use whenever the user asks to create, open, draft, update, or review a pull request. Enforces issue discovery and linkage, Conventional Commit titles, release-note quality, complete validation evidence, and safe pushing.

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 the UX of custom-code Databricks Apps (AppKit/React) data screens — KPI/overview pages, reports, charts, tables, and Genie/chat data assistants — mapped to concrete AppKit components. Use when BUILDING or reviewing the UI of an AppKit/React app that displays data or answers data questions: choosing genre, layout, charts, KPIs, semantic color, required states (loading/empty/error), IBCS notation, and AI-result trust (showing generated SQL/sources for Genie/chat). A plain "create a dashboard" request means a managed AI/BI (Lakeview) dashboard → use databricks-aibi-dashboards, NOT this skill. Also NOT for non-data frontend (forms, settings, auth, marketing) or scaffolding/build/deploy (→ databricks-apps). Complements databricks-apps; use it alongside whenever a custom app has a chart, table, KPI, report, or Genie/chat/AI surface.

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, manage, and query Databricks Genie Agents — curated, per-data natural-language agents (formerly Genie Spaces): build, export/import, migrate across workspaces, and ask questions of a *specific* Agent via the Conversation API. For general data questions or finding data across your workspace, use databricks-data-discovery (Genie One) instead.

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。

Answers business questions about the user's own spreadsheet or data export (CSV, TSV, XLSX from a CRM, Shopify, Stripe, QuickBooks, ad platforms, HR or payroll systems) correctly and auditably. Profiles every file first (grain, duplicate keys, embedded Grand Total rows, text-stored numbers, mixed currencies, UTC timestamps, Excel serial dates, hidden rows), states the metric definition used, computes every number in SQL or pandas instead of mental math, checks joins for fan-out, reconciles to a known total, and returns the query, filters, row counts, and rows behind the answer. Use this whenever the user says "analyze this spreadsheet", "how many...", "what's the total in this export", "which customers...", "pivot this", "revenue by month", "top 10", "what's our churn/MRR/AOV", or asks any question about their data, CSV, or Excel file, even a quick one. Also use when they ask to change values in a data file.

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。

Creates structured hiring scorecards for any role. Takes job title, requirements, and team context. Generates comprehensive scorecard with weighted scoring rubric, interview questions per competency, evaluation matrix, red/green flags, and reference check questions.

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 inbound leads (form fills, demo requests) and score based on ICP fit, intent, and urgency. Auto-generates qualification questions, routes to right rep, and suggests personalized first touch. Use for qualifying and routing inbound leads at scale.

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。

Prepares pull requests by running quality gates, drafting descriptions, and validating tests. Use when completing a feature and ready for 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。

Probe memory/summary clarity via dual anchor questions: task progress, info gaps. Use when verifying session state or summary before handoff or compression.

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。

Guides when to ask clarifying questions versus proceed autonomously. Use to reduce unnecessary clarifying questions when intent is clear.

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。

Routes substantive ML, AI, data, scientific-computing, and software-engineering requests to the smallest useful set of managed repository skills. Invoke proactively when a request names or implies a package, framework, model family, dataset, modality, workflow, backend, deployment target, evaluation method, or implementation approach that may benefit from repository guidance, even if no repository is named. Narrow progressively from area to family to repository root: inspect only the one or two most likely area pages; compare candidates by capability, task surface, model/data format, training versus inference versus evaluation intent, runtime constraints, and root-skill description; then open only the selected root and relevant sub-skills, references, or scripts. Select multiple repositories only when each adds a distinct capability. Do not load the whole collection, treat dependencies or incidental integrations as capabilities, choose by name alone, or force a match when no exact taxonomy family applies.

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。

CI/CD pipeline attack hunting (GitHub Actions focus) - pwn requests (pull_request_target), script injection, self-hosted runner takeover, cache poisoning, OIDC-to-cloud token theft, poisoned pipeline execution. Wiki-first, FIND schema output.

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。

Drive responsible disclosure of a proven finding to a CVE. Package the report, find the vendor contact, report privately, coordinate a timeline, request the CVE (vendor CNA / GitHub / MITRE), and publish an advisory. Closes the research loop. Triggers - "disclose", "request a cve", "report this to the vendor".

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。