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概要と使いどころ
Apply an emotional resonance lens to any UI. Use when a design is technically correct but flat — to identify what's missing and prescribe specific changes at the copy, motion, and interaction layer.
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。
Email triage system that handles both one-time setup and recurring triage in a single skill. Auto-detects state: if no knowledge base exists at ${WORKSPACE}/Email/, runs an 8-section onboarding interview (grill-me discipline, one question at a time) to build a 7-file personalized KB, then offers to run triage immediately. If the KB already exists, skips setup and goes straight to triage — searches recent emails, classifies them via the user's taxonomy, researches new senders, generates TAKE IT/WORTH/PASS/FLAG recommendations, drafts replies (NEVER sends), delivers a report, and updates the KB. Use with 'update' argument to refresh preferences. Setup triggers: 'set up my inbox', 'configure inbox triage', 'set up my email system', 'configure email triage', 'build my email knowledge base', 'initialize email management'. Triage triggers: 'triage my inbox', 'inbox triage', 'check my email', 'run email triage', 'process my inbox', 'what's new in my email', 'handle my email', 'email triage'.
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。
Blog strategy development including topic cluster architecture with hub-and-spoke design, audience mapping, competitive landscape analysis, AI citation surface strategy across ChatGPT/Perplexity/AI Overviews, distribution channel planning (YouTube, Reddit, review platforms for GEO), content scoring targets, measurement framework, and content differentiation through original research and first-hand experience. Use when user says "blog strategy", "content strategy", "blog positioning", "what should I blog about", "blog topics", "content pillars", "blog ideation".
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。
Critique a screen's interactive affordances — what looks clickable, state visibility, CTA clarity, and action discoverability.
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 what content a product needs, how it should be structured, and who owns it.
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。
Generates a fully structured, project-specific CLAUDE.md by scanning the repo for signal files (package.json, Makefile, .github/workflows/, .env.example, etc.), inferring stack, commands, architecture, and conventions, then asking at most 3 targeted questions for what cannot be inferred. Use whenever the user says 'create a CLAUDE.md', 'my CLAUDE.md is blank', 'generate project context', 'initialize CLAUDE.md', 'set up Claude context for this repo', 'fill in my CLAUDE.md', or any variation where someone needs their project context documented for Claude. If a CLAUDE.md already exists with content, runs a diff-and-merge flow before writing.
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。
Captures and organizes chaotic brain dumps into a structured, actionable system with zero information loss. Use this skill whenever the user says 'capture this', 'brain dump', 'let me dump some ideas', 'I've got a bunch of thoughts', 'here's everything on my mind', 'idea dump', 'let me get this out of my head', 'I need to organize my thoughts', 'here's what I'm thinking', or any variation where someone is unloading a messy stream of ideas, tasks, thoughts, and plans wanting them turned into something coherent. Also trigger when the user pastes or dictates a long, unstructured block of mixed ideas — even without the exact phrase — the intent is the same. Fast-to-action by design: no upfront intake. Output is four sections (Projects/Ideas, Tasks, Connections, How I Can Help) ending with a directive question. Asks at most one mid-organization clarifying question when a single item is genuinely ambiguous between task and project.
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 editorial calendars for blogs with topic clusters, publishing schedules, content decay detection, freshness update plans, seasonal opportunities, content mix formula, template integration, and distribution scheduling. Plans monthly or quarterly calendars optimized for SEO topic authority and AI citation freshness requirements (30-day update cycles). Use when user says "editorial calendar", "content calendar", "blog calendar", "publishing schedule", "blog plan", "content plan", "what should I write".
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。
Generates a fully structured SEO content **outline** (not a finished brief) and exports it as a formatted .docx Word document. The output is a skeleton for a writer to fill in — section headings, topic prompts, angles — not pre-written paragraphs. Use this skill whenever a user provides a blog title, focus keyword, domain URL, or any combination of those and asks to generate an outline, brief, blog brief, SEO brief, article structure, or content plan. Also trigger when the user says "create a brief for X", "generate an outline for [topic]", "make a content brief", "I need a brief for [URL or keyword]", or pastes a title and asks what the structure should look like. This skill handles input validation, domain analysis, keyword enrichment, audience inference, archetype-aware section selection, and full .docx generation — always use it rather than writing ad-hoc outlines.
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 images, websites, and Figma files to extract their design and generate a `design.md` with token system, component inventory, and reconstruction notes. Use this skill whenever the user wants to understand, document, replicate, or audit the design of something visual: a screenshot, a URL, a Figma link, a Pinterest reference, a mockup, a competitor's site, a component, a dashboard, a landing page. Also when they ask 'extract the design system from X', 'document the style of Y', 'analyze this visually', 'convert this image into tokens', 'help me replicate this design', 'what palette does this site use', 'how is this built'. Also for single elements: 'copy this navbar', 'recreate this illustration', 'give me a prompt to regenerate this graphic' — element mode outputs a focused element.md, with token-grounded image-model prompts when the element is visual art. If the user brings any visual source and wants to understand it at a design level — this skill should activate.
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 your X (Twitter) audience and niche from real data. Pull a handle's recent tweets (yours or a competitor's) with likes, replies, and views, see which formats and hooks are working, read the repliers on a tweet (X gates likers, so repliers are the signal), and scan a niche query for top tweets. Powered by Apify, no login. Triggers on "analyze my tweets", "what is working on X", "read the replies", "competitor tweets", "who is engaging". Not for writing a tweet (use x-post-writer).
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 assessing the architectural health of a codebase — before a major refactor, when onboarding to an unfamiliar repo, after rapid growth, when planning a redesign, or to surface structural strengths and risks before they become expensive. Not for fixing what it finds, and not for reviewing a branch diff.
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。
Cut a paad release — pick the semver bump from what is in [Unreleased], run make release, merge, tag, and verify the published plugin
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 reviewing current branch for bugs before pushing or merging, when wanting a thorough multi-agent review of local changes, or when preparing work for human review. Not for codebase structure, not for code style, and not for fixing what it finds.
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。
EXPERIMENTAL. Use when looking for meaningfully duplicated logic in a codebase, especially duplicate behavior hidden behind different names, different syntax, different control flow, or independently evolved implementations. Not for style issues, not for syntactic clone detection, and not for fixing what it finds.
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。
EXPERIMENTAL. Use when code needs a security review against the OWASP Top 10:2025 — access control, misconfiguration, supply chain, cryptography, injection, insecure design, authentication, integrity, logging and alerting, and mishandled exceptional conditions. Not for penetration testing a running system, not for infrastructure-only scanning, and not for fixing what it finds.
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。
Computes a numeric or categorical answer to a quantitative data-science question by cleaning and analyzing local data files (CSV, Excel, TSV, and scientific formats .npz/.fits/.h5) with pandas, numpy, and scipy. Use whenever a task ships its own dataset (in whatever local directory it provides) and asks you to derive a value via statistical, geospatial, temporal, ratio, percentage, growth-rate, correlation, signal-processing, orbital, or forecasting analysis. Spans domains including archeology (demographics, paleoclimate proxies, radiocarbon dating, historical conflicts); biomedical/bioinformatics (tumor histology, genes, proteins, peptides, genomic variants); environmental (water quality, bacterial/Enterococcus exceedance, rainfall correlations, environmental justice); legal/consumer (fraud, identity theft, consumer complaints by state/metro); wildfire (incidents, causes, suppression costs, acres burned, fatalities, geospatial intersections); and astronomy/heliophysics/space weather (satellite telemetry TLE/Swarm/SP3, indices OMNI/GOES, solar activity, atmospheric density, orbital mechanics, forecasting).
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 asks to audit what's wrong with a project, "make it right", "看看项目出了什么问题", "为什么用户的需求还没上线", "为什么没提交App Store", "为什么没新build", or wants a holistic state-of-the-project check covering unmerged branches, stalled PRs, failed GitHub Actions, stale builds, plan drift (TODOS.md / ROADMAP), unreleased commits, and log errors. Runs read-only investigation, presents a grouped checklist, fixes only after explicit user confirmation. Aware of the Cathier iOS app workflow (Xcode + fastlane + auto-merge @claude PRs from in-app feedback).
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 tune any dev machine, fresh or drifted, on macOS, Linux, or Windows: report what's missing, install only that, then fix PATH, duplicate runtimes, and shell config. Don't use for Dockerfiles, CI images, or single package installs.
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。
Turn the questions and instructions a user keeps typing into a project into short slash-command skills, mined from their real Claude Code, Codex and Cursor session history and git log. The shortcuts load in Claude Code, Codex and Cursor. Use when the user says they ask the same things every day, wants an FAQ or shortcuts or abbreviations for a project, wants to "stop writing the whole command", or asks what they repeat most.
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 channels the reasoning of Walter C. Willett, nutrition epidemiologist at Harvard University. Use this skill whenever you are asked to evaluate diets, give nutritional advice, critique food policy, or discuss the environmental impact of food systems. Trigger this skill for topics like macronutrient quality (fats vs. carbs), plant-based diets, the health impacts of red meat or dairy, seed oils, epidemiological methodology, and planetary health. Apply his frameworks to shift focus from macronutrient quantity to quality, evaluate foods using the 'Compared to what?' rule, and prioritize public health over personalized nutrition fads.
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。
Applies the philosophical frameworks of Friedrich Nietzsche (19th-century German philosopher, author of Thus Spoke Zarathustra). Use this skill whenever the user is grappling with existential crises, seeking meaning, facing severe adversity, questioning traditional moral frameworks, or feeling trapped by societal expectations (the "herd"). Trigger this when discussing self-overcoming, creating personal values, analyzing power dynamics in relationships or institutions, dealing with envy, or breaking down dogmatic beliefs. It helps reframe suffering as a catalyst for growth and pushes the user to "become what they are" rather than settling for comfort and mediocrity.
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。
Applies the nutritional epidemiology and public health frameworks of Frank B. Hu (nutrition epidemiologist, Harvard University). Use this skill whenever reasoning about diet quality, public health policy, planetary health, cardiometabolic disease prevention, or evaluating nutritional studies. Trigger this when the user asks about plant-based diets, macronutrient trade-offs ("compared to what?"), the impact of the food environment, or lifestyle factors for longevity. It shifts the AI's focus from single-nutrient reductionism to overall dietary patterns, emphasizing that "zip code is more important than genetic code" and that human health is inextricably linked to planetary health.
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。
Applies Judea Pearl's causal reasoning frameworks to distinguish correlation from causation, evaluate AI capabilities, and make counterfactual decisions. Reach for this skill whenever Claude encounters questions about causal inference, structural causal models, the limitations of deep learning, AGI, experimental design, covariate selection, or personalized decision-making. Trigger this skill for topics involving Bayesian networks, the do-calculus, the Ladder of Causation, or when a user tries to answer 'what if' or 'why' questions using purely observational data. Pearl's principles are essential for moving beyond probability calculus into true causal understanding.
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。