1.5万 件 ・ 関連度順
概要と使いどころ
Type-safe URL query state management with nuqs 2.x. Use when writing or reviewing code that uses useQueryState, useQueryStates, URL search params, query parameters, nuqs parsers, createLoader, createSearchParamsCache, createSerializer, or URL state in Next.js, React, Remix, React Router, or TanStack Router.
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 Gcp Bigquery Deep — google BigQuery job analysis, slot utilization, storage optimization, materialized views, BI Engine capacity, and query performance diagnostics via bq CLI and gcloud.
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 Athena — aWS Athena query execution analysis, workgroup management, Data Catalog integration, and cost-per-query tracking. Covers query history, performance optimization, workgroup quota management, saved queries, and data scanned analysis.
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 Bigquery — google BigQuery job analysis, slot utilization, cost analysis, dataset management, and query optimization.
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。
Optimize Entity Framework Core queries by fixing N+1 problems, choosing correct tracking modes, using compiled queries, and avoiding common performance traps. Use when EF Core queries are slow, generating excessive SQL, or causing high database load.
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 polished, validated architecture, workflow, sequence, data-flow, and lifecycle/state diagrams as explorable standalone HTML with inline SVG, dark/light themes, optional trace motion, and PNG/JPEG/WebP/SVG/WebM export. Accept plain-language requirements or pasted Mermaid flowchart, sequenceDiagram, and stateDiagram input; inspect repository evidence when the diagram must reflect real code. Use when the user asks to visualize system architecture, infrastructure, cloud/security/network topology, technical workflows, API call sequences, request lifecycles, data pipelines, ETL/ELT, data lineage, state machines, or to convert/beautify Mermaid.
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。
Read, write, and query Apple Health data using HealthKit. Covers HKHealthStore authorization, sample queries, statistics queries, statistics collection queries for charts, saving HKQuantitySample data, background delivery, workout sessions with HKWorkoutSession and HKLiveWorkoutBuilder, HKUnit, and HKQuantityTypeIdentifier values. Use when integrating with Apple Health, displaying health metrics, recording workouts, or enabling background health data delivery.
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 critical rationalist epistemology (Popper, Deutsch) to evaluate reasoning, identify errors, and refine understanding. Use when the user explicitly requests help with reasoning - phrases like "help me think this through", "does this make sense", "any flaws in this", "what am I missing", "critique this", "is this reasoning sound", "stress test this idea", "devil's advocate", or any request to evaluate arguments, identify logical problems, or improve thinking. Also use when errors in reasoning are significant enough to materially affect the user's goals, even if not explicitly requested.
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 this skill when writing a pull request description, change summary, or release notes in Japanese for this project. Trigger words: PR 説明, プルリク, 変更サマリ, リリースノート, PR 文章, レビュー依頼, 日本語で説明, pull request.
Patterns for scaling read-heavy Convex apps to millions of users. Use when optimizing bandwidth, reducing query costs, fixing slow queries, creating digest tables, replacing reactive subscriptions with one-shot fetches, adding compound indexes, debouncing writes, rate-controlling backfills, or running npx convex insights. Trigger when users mention "scale", "bandwidth", "performance", "optimize", "slow queries", "expensive queries", "digest table", "denormalize", or "thundering herd" in the context of Convex.
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。
BullMQ expert for Redis-backed job queues, background processing, and reliable async execution in Node.js/TypeScript applications. Use when: bullmq, bull queue, redis queue, background job, job 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。
BullMQ expert for Redis-backed job queues, background processing, and reliable async execution in Node.js/TypeScript applications. Use when: bullmq, bull queue, redis queue, background job, job 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。
Azure Monitor Query SDK for Java. Execute Kusto queries against Log Analytics workspaces and query metrics from Azure resources.
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。
Read and drive Agentic Table (magic table / due-diligence) sheets through the unique-cli agentic-table command. Use when the user or task involves an Agentic Table: inspecting a sheet's state, a cell's value or lock state, a cell's edit history or its export artifacts; writing text into a specific cell; or running the full loop — creating a sheet, importing a questionnaire and sources, waiting for the agent to answer, and exporting the result. Access is enforced per sheet by the platform and varies from sheet to sheet; a denial is reported as `agentic-table: permission denied`.
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。
Handle pull requests and review comments using GitHub CLI (gh). Use when the user wants to check PR comments, address review feedback, reply with commit hashes, or work with pull 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。
Call MCP (Model Context Protocol) server tools on the Unique AI Platform using the unique-cli mcp command. Use when the user asks to invoke, call, or execute an MCP tool, or when they need to send a JSON payload to an MCP server through the CLI. The JSON payload is forwarded 1:1 to the platform's MCP call-tool API.
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 presents an idea/plan/proposal and wants a specific 16-minds (MBTI) personality to ask probing questions back — instead of giving an answer. Triggers on Japanese phrases like 「ENTPでツッコんで」「INFJに問い詰めて」「ENTJ視点で質問して」「このアイデア叩いて」, English equivalents like "as ENTP, question this" / "INFJ would ask what?", or 16-minds commands with a `--ask` flag. AIに「答えさせる」のではなく「問わせる」ためのSkill。ユーザーが思考を整理したい時に使う。
Create, edit, or debug parametric 3D CAD parts in CadQuery (Python) that export to STEP for SolidWorks. Use when the request involves CadQuery, .step/.stl export, or modelling a physical part — enclosure, bracket, PCB, motor mount, cam, gear. Also use when a STEP will not open in CAD, or geometry looks correct in STL but is invalid as a solid. Applies a verification discipline before export and documented OCC pitfalls.
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。
SEO + GEO (AI-search) + brand-entity desk (Busabase App-in-Skill) — wired to Google Search Console for a dashboard over search analytics and an agent-prepared SEO opportunities review queue, plus an AI-visibility tracker (are we cited in ChatGPT / Perplexity / Gemini / Claude / Copilot answers), a GEO content-optimization queue gated by geo-qa, and an entity / knowledge-panel readiness checklist. Use when the user invokes $kelly-seo or /kelly-seo, mentions SEO, Google Search Console, GSC, search analytics, search performance, queries, keywords, rankings, positions, impressions, clicks, CTR, striking-distance queries, title/meta rewrites, content briefs, internal links, SEO opportunities review, GEO, generative engine optimization, AI search, AI visibility, being cited by AI answer engines, ChatGPT/Perplexity/Gemini/Claude/Copilot citations, brand entity, knowledge panel, Wikidata, schema.org, or entity readiness.
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。
Personal App-in-Skill voice-of-customer desk (Busabase App-in-Skill) aggregating user feedback from support email, Discord/Slack communities, X replies, app-store reviews, surveys, and interviews into clustered feature requests and a roadmap decision queue. Use when the user invokes $kelly-feedback or /kelly-feedback, or mentions user feedback, voice of customer, feature requests, roadmap decisions, feedback clustering, feedback triage, request dedupe, changelog replies, decline replies, or reviewing what users are asking for.
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。
MUST USE when source footage or a material folder is provided and material understanding or 03_analysis generation is needed. Trigger not only on explicit analysis requests ('分析して', '素材を見て') but also when the user points at footage and says things like 'この動画で', 'この素材で', or any request that requires understanding the provided media before planning or editing.
Unified pull request workflow: prepare a safe branch, run read-only review, fix Required findings, create/update a GitHub draft PR, and verify CI plus automated review comments. Subcommands: `create` (simplify + PR, skip code review), `review` (read-only findings only), `fix` (Required fixes + commit, no push), `simplify` (simplification only), `verify` (existing PR checks/reviews only). Use when creating or reviewing PRs, self-reviewing changes, simplifying PR changes, or requesting "PR作成", "レビュー", "簡素化". Do NOT use for responding to review comments or a lightweight review of the current working diff without the PR workflow (use the built-in /code-review instead).
Write or edit Japanese articles, reports, guides, and public-facing drafts so the argument is clear and the prose reads naturally. Preserve the author's meaning, evidence, and voice when revising. Use for requests to write from a topic or notes, remove AI臭 / AIっぽさ, improve awkward wording or structure, or format notes as 箇条書き, チーム共有, 社内共有, a decision note, handoff, Slack post, or Teams post. For existing prose, ask Gemini through Antigravity CLI to rewrite naturally by default, then audit against the source; use the current model if unavailable. Do NOT use for ordinary Japanese answers, progress updates, technical explanations, code review, English-only prose that is not a bullet-formatting request, or an explicitly incompatible format.
Hand off a task with only the context needed to continue in a fresh session. Use for "handoff", "引き継ぎ", "別セッションへ渡す", or "別マシンで続ける". The orca subcommand launches an independent Orca workspace or terminal tab; without it, produce a paste-ready prompt backed by a verified remote branch or PR. Do not launch sessions for capability questions or design requests.