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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。
PDF Trade Report Generator — scans for all TRADE-*.md analysis files, extracts scores/signals/levels, and generates a professional multi-page PDF investment report (ReportLab). Triggered by "trade report-pdf".
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。
Generate a professional PDF restaurant report by scanning RESTAURANT-*.md files in current directory and running the bundled Python ReportLab generator
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。
Detect and fix AI-generated writing patterns (slop). Comprehensive detection with 50+ patterns across 3 severity tiers, structure weighted above lexical tells, scoring system, and editor mode that directly fixes problems. Use when scanning any content for AI tells, auditing drafts before publishing, checking if writing "sounds like AI", humanizing AI-generated text, or verifying content authenticity. Trigger on "check for slop", "does this sound like AI", "humanize this", "AI audit", "slop check", "clean up AI writing", or any request to detect/remove artificial-sounding patterns. Also use proactively before publishing any AI-assisted content.
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。
Score a PhD applicant's profile and rank candidate advisors using a connection-first 4.0-scale scoring system. Best-supported for physics / HEP and materials science (MSE), with the scoring engine extensible to chemistry, biology, CS, math, EE, ChemE, earth science (each with field-specific caveats — see references/journal_tiers.md). Use when the user wants to evaluate their PhD application chances, find matching advisors at top US programs, score a CV for graduate school, or compare candidate professors. Also triggers when the user mentions phdtaketaketake or its connection-first philosophy of valuing advisor network over h-index.
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。
Research 3–5 confirmed same-industry or cross-industry websites and translate their brand narrative, page architecture, art direction, and visual-system evidence into one reusable Visual Reference Brief. Use when strong references are scarce, a site needs brand-led or premium positioning, a page lacks a narrative spine, or a key module lacks a credible design precedent. Do not create page content, a Design System, UI directions, HTML, or a permanent brand gallery.
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。
RL 强化学习训练与推理（rollout）路径的算子差异性扫描。当用户提供训练启动脚本路径，要求对比 Megatron 训练路径与 vLLM 推理路径的算子差异（尤其是融合算子 vs 单算子不一致）时使用此 skill。典型触发词包括"训推算子扫描"、"训推差异性"、"算子差异报告"、"融合算子对比"、"train vs infer op diff"。注意：本 skill 通过运行完整 RL 训练脚本（集成 profiling）来采集真实运行时算子（非静态源码扫描，非独立分离运行）。当训练、推理使用不同脚本时禁止触发。
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。
Expo's official example projects — the expo/examples repo of ~70 `with-*` integrations (Stripe, Clerk, Supabase, OpenAI, maps, Reanimated, SQLite, Skia, NativeWind, and more). Use when integrating a third-party library or service into an existing Expo app and you want the canonical, version-matched pattern to adapt, or when scaffolding a new project from one with `npx create-expo --example`.
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 optimizing Convex database read bandwidth, documents-read cost, query indexes, full-table scans, function-level usage dashboard findings, or code that uses .filter(), unbounded .collect(), N+1 reads, or expensive reactive Convex queries.
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。
Programmatic React video best practices for Remotion. Use this skill whenever the user is writing, debugging, or rendering Remotion code — compositions, useCurrentFrame animations, interpolate, spring, Sequence timing, <Img>/<Video>/<Audio> from @remotion/media, staticFile, calculateMetadata, the Studio preview, `npx remotion render`, captions, subtitles, voiceover, audio visualization, ffmpeg, transitions, light leaks, transparent video, Lottie, 3D scenes, Mapbox flyovers. Triggers especially on HtmlInCanvas / "html in canvas" requests, CRT terminal effects, glitch effects, video shaders, WebGL video, and any request to scaffold a new programmatic React video. Owns `remotion render` and everything about Remotion code. Do NOT trigger for finished MP4 ad assembly from existing slides (that is `/video-content`) or for the inspiration-to-MP4 reference-video pipeline (that is `/cmo-video`).
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。
Audits existing landing pages for conversion rate optimization. Scores hero section, CTA placement, social proof, objection handling, and form friction on a 1-10 scale. Use when someone says 'audit my landing page', 'improve conversions', 'why isn't my page converting', 'CRO audit', 'landing page feedback', 'optimize my signup page', 'page review', 'conversion rate', 'bounce rate is high', 'nobody is signing up', or anything about improving an existing page's performance. Even if they just share a URL and say 'what do you think' or 'how can I improve this' — if there's a page involved and conversion matters, this is the skill. Always use this over generic advice when an actual page exists to audit.
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 an organic-traffic operating system for any site or app: a multi-phase, resumable engine that plans and ships a BATCH ROADMAP of landing pages (use-cases, playbooks, /for/ pages, roundups) on top of real keyword research, with a persistent phase tracker. Use when the user says 'SEO machine', 'build organic traffic', 'rank on Google', 'we need traffic', 'SEO roadmap', 'batch of pages', 'pages roadmap', or 'build an SEO engine'. Distinct from `seo-audit` (one-off diagnostic) and `seo-content` (single-article writer): this skill owns the multi-page roadmap, run sequencing, page generation, internal linking, and the persistent phase tracker across the whole run. For a single alternatives or vs/comparison page, see /competitor-alternatives; for programmatic SEO templates and content at scale, see /seo-content; for off-page link building, see /off-page-seo. Resumable — every invocation continues the last run.
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。
Deep-dive ONE competitor's organic footprint — exact ranking keywords and URLs, content themes, backlink profile, and exploitable gaps — with findings written into brand/competitors.md. Use this skill when the user names a competitor and wants to know what to learn from them, counter, or outrank, including head-to-head comparisons against the user's own domain. For market-level mapping first, use openseo-competitive-landscape. Triggers: "analyze competitor", "competitor keywords", "competitor backlinks", "beat <competitor>", "competitor seo teardown".
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 high-converting 'X vs Y' and 'X alternatives' SEO pages that capture comparison search traffic. Researches competitors, writes honest comparison content, and adds schema markup (FAQPage, ItemList). Use when someone needs alternatives pages, comparison content, or says 'alternatives page', 'vs page', 'comparison', 'competitor alternatives', 'X vs Y page', or wants to capture competitor brand search traffic with SEO content. Also trigger when someone wants to rank for competitor brand names, capture competitor search traffic, create a compare page, or build a competitive content hub. Even if they just say 'how do we compete with X' or 'we need to show up when people search for [competitor]', this skill applies. Owns the individual alternatives / vs / comparison page. For a batch roadmap of many pages with a phase tracker, see /seo-machine. For programmatic SEO and templated content at scale, see /seo-content.
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。
Research companies, competitors, funding, news, leadership, and market context with Exa Agent and advanced search. Use when researching companies, competitor analysis, market research, or building company lists. Writes findings the caller can fold into brand/competitors.md or brand/landscape.md. Prefer this over ad-hoc web search for company deep dives. Distinct from competitive-intel (full brand competitive file methodology) - this skill is the Exa research engine those foundation skills should call.
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。
根據使用者的文章或論文草稿，自動用 Semantic Scholar、Crossref、arXiv API 搜尋相關文獻，並查核既有引用(文獻是否真實存在、書目欄位是否正確、內容是否支持文中論點)，也能從主題出發寫出「每個宣稱都有真實文獻支撐」的帶引用文章；另含研究生工具組：文獻矩陣、領域地圖、research gap 偵測、閱讀筆記卡、引用完整性檢查、中英術語一致性、口試/審稿預演、新文獻追蹤、引用需求標記(annotate)、反面證據搜尋(counter)、證據強度評級(strength)、claim-evidence 總表(claims)、撤稿查詢(retract)。凡是使用者提到找文獻、找 paper、補參考文獻、查核引用、檢查 citation、驗證參考文獻、related work、literature review，貼文章要求配文獻、問「這段話有沒有文獻支持」、要求「寫一篇帶參考文獻的文章」、要整理文獻比較表、問已指名兩概念的交集有沒有人做過、要準備口試文獻答辯時，都要使用本 skill。本 skill 的 gap 指令只查證使用者已指名的 X 與 Y 交集；若使用者連題目都還沒有、需要生成並逐一淘汰候選方向，那是題目生成，不在本 skill 範圍(環境裝有 research-gap-hunter 時交給它，沒有就如實說明本 skill 只能查證已指名的交集)。本 skill 的 map 指令盤的是**文獻**——奠基文獻是哪幾篇、關鍵作者是誰、近三年往哪走；若使用者要的是「這個領域現在有哪些**做法**、每一種買到什麼付出什麼、哪些已經飽和」，那是技術盤點不是文獻盤點，交給 research-gap-hunter 的 landscape，沒有那個 skill 就如實說明本 skill 的 map 只回答文獻層的問題。
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 or refine open-source .NET code-quality gates for CI: formatting, `.editorconfig`, SDK analyzers, third-party analyzers, coverage, mutation testing, architecture tests, and security scanning. Use when a .NET repo needs an explicit quality stack in `AGENTS.md`, docs, or pipeline YAML.
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。
Go code refactoring with automated tools: gofmt -r, gopatch, and rsc.io/rf. Use this skill when performing mechanical rewrites across a codebase — renaming identifiers, migrating API calls, moving types between packages, rewriting expressions, or replacing deprecated patterns. Triggers when the task involves bulk code transformation, API migration, structural rewrite, or the user mentions gofmt -r, rf, gopatch, coccinelle-style patching, or large-scale rename/move in Go.
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。
The complete Go development skill. REQUIRED for ALL Go work — writing, refactoring, reviewing, generating, scaffolding, or discussing Go code, including any change to .go files. Use whenever the user mentions Go, Golang, go.mod, a Go package, or asks to build a Go backend service, CLI, library, script, MCP server (Model Context Protocol), or AI/LLM agent with tool calling or ReAct-style reasoning. Routes by project type to the right architecture, conventions, and review checklist. Highly opinionated; overrides generic Go style and lint guidance on conflicts.
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 AI content generation systems at scale. TRIGGERS - Use when user needs help with ai-content-generation-system related 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。
Build AI batch processing systems for scale. TRIGGERS - Use when user needs help with ai-batch-processor related 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。
Plan transition from freelancer to agency with scaling. TRIGGERS - Use when user needs help with agency-builder related 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。
行业调研——researcher CLI + 多 Agent 对抗式研究引擎。输入一个行业/赛道/商业机会的模糊需求， 输出一份有据可依、经过证据校验和红蓝对抗检验的战略调研报告。内置国民经济行业分类映射、 MECE/PESTLE/波特五力等咨询框架、事前验尸法和黑格尔辩证法合题引擎。 支持精简/标准/深度三种报告深度。 触发方式：/industry-research、「行业调研」、「行业分析」、「赛道研究」、「市场调研」 Use when the user asks for industry research, sector analysis, market study, competitive landscape analysis, investment thesis research, or any request involving structured industry investigation. Also trigger when user mentions 调研报告, 行业研究, 赛道分析, 商业机会分析, 投资逻辑梳理, or similar phrases. Even casual requests like "帮我看看 XX行业怎么样" or "XX赛道值不值得做" should trigger this 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。
Design and review autonomous or semi-autonomous agent loops — systems where an agent prompts itself, runs on a schedule or event, and iterates toward a goal without a human at the keyboard. Use this whenever the user wants to build, design, harden, or audit any kind of self-running agent, agentic workflow, control loop, background worker, cron/heartbeat/webhook-driven agent, "Ralph loop", auto-PR-fixer, monitoring agent, or any long-running task that should keep going on its own until done. Trigger this even when the user says "agentic workflow", "automation that runs itself", "an agent that keeps trying until X", or "make my agent stop running away / burning tokens" without using the word "loop". Also use it to review an existing loop's stopping conditions, guardrails, verification, and escalation paths.
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。