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概要と使いどころ
Read a story file and implement it. Loads the full context (story, GDD requirement, ADR guidelines, control manifest), routes to the right programmer agent for the system and engine, implements the code and test, and confirms each acceptance criterion. The core implementation skill — run after /story-readiness, before /code-review and /story-done.
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 should be used when a session's job is to DRIVE OPEN PRs TO MERGE rather than to write new code — "close out the open PRs", "review and fix the open PRs", "what's blocking our PRs", "which PRs are mergeable". It owns the In Review column: it reads each PR's gate status, verifies and fixes review findings on PRs OTHER sessions built, replies in-thread, and stops at the merge gate for the user's per-PR approval. Do NOT load it for building a feature and opening its PR — that is a build session (`genesis-development`).
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 when Genesis writes as itself — outreach, public content, community posts, emails, DMs. Not for writing in the user's voice (that's voice-master). Activate when Genesis is the author, not the ghostwriter.
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 or improve a Skill (an executable, reusable capability with a ``SKILL.md`` plus optional ``scripts/``, ``references/``, and assets). Trigger this skill whenever the user wants to: - Capture a workflow they keep repeating into a fresh Skill - Polish an existing Skill's prompt, description, or examples - Tighten when-to-trigger wording so the model invokes the Skill more reliably - Discuss the Skill format, frontmatter, or how progressive disclosure works Do not wait for the user to say "skill-creator" verbatim — phrases like "turn this into a skill", "let's make a reusable thing for this", "improve my skill", or "tweak the description for this skill" should all reach 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。
Audit a .glb or .gltf and make it small, correct, and fast to load in a browser, with a measured before/after report. Use when a model is "too big" or "slow to load", when the user asks to "optimize this GLB", "compress this glTF", or "export for web", or when they mention Draco, meshopt, gltfpack, KTX2, Basis, texture VRAM, draw calls, or a Blender / CAD / photogrammetry / Pascal export headed for Three.js, React Three Fiber (drei useGLTF), Babylon.js, or model-viewer. Covers inspection, spec validation, geometry and texture compression, scene-graph cleanup, and the correctness checks (metres, Y-up, node names, animations, PBR fidelity, alpha modes, vertex colors) that must not regress. Not for editing or modelling geometry, authoring or laying out a scene, generating 3D from text or images, converting from FBX/OBJ/CAD, or debugging a runtime frame rate that has nothing to do with asset size.
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。
Executes an approved implementation plan through fresh implementer and reviewer agents for each task, with explicit handoffs, focused tests, and task-by-task integration. Use for multi-task work where independent agent context improves implementation and review quality. Not for a single small edit, an unresolved design, or a failure that still needs root-cause 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。
Executes an existing implementation plan task by task, preserving its interfaces and constraints, running focused checks after each slice, and stopping when the repository differs from the plan. Use when a written plan or approved checklist already exists. Not for inventing the plan, debugging an unexplained failure, or broad unscoped cleanup.
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。
Processes code review feedback by classifying each finding, reproducing or validating it against the real contract, applying the smallest in-scope fix, and re-running focused proof. Use after comments arrive on a diff, pull request, design, or implementation. Not for requesting a first review or debugging an unrelated failure.
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 Angular code and provides architectural guidance. Trigger when creating projects, components, services, or HTTP communication, or for best practices on reactivity (signals, linkedSignal, resource, httpResource), forms, dependency injection, routing, SSR, accessibility (ARIA), animations, styling (component styles, Tailwind CSS), testing, naming conventions, or CLI tooling.
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。
Quick mode for the rest of the session. Instead of CI's full checks, a change runs only the checks it can affect (format, lint, types and build, its own tests, and every unit, integration, flow and browser test that reaches the code it touched), and the rest of the suite is left for a full run such as a pull request's CI. Runs only when the user types it, and `/first-pass:quick off` turns it off.
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 a file has been uploaded but its content is NOT in your context — only its path at /mnt/user-data/uploads/ is listed in an uploaded_files block. This skill is a router: it tells you which tool to use for each file type (pdf, docx, xlsx, csv, json, images, archives, ebooks) so you read the right amount the right way instead of blindly running cat on a binary. Triggers: any mention of /mnt/user-data/uploads/, an uploaded_files section, a file_path tag, or a user asking about an uploaded file you have not yet read. Do NOT use this skill if the file content is already visible in your context inside a documents block — you already have 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。
Read this skill before the first step of any request to do something in an app on the person's own computer (Notes, Finder, System Settings, any desktop app), to look at their screen, or for "computer use". Computer use (desktop control) lets Claude take screenshots of the person's desktop and control it with clicks, typing and scrolling through the Claude desktop app; its tools are named mcp__computer-use__* when the session runs in the desktop app and mcp__remote-devices__computer_* when a cloud session is linked to the person's computer; before a conversation is linked there may be no such tools, only an enable__mcp__remote-devices__Claude_Browser tool, which links it. It covers getting linked, picking the right tool, the access flow, and what to do when computer use is off or out of reach. It is not for websites, which go through Claude in Chrome or the built-in browser and their own 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。
Read this skill before the first step that uses the built-in browser, the browser pane inside the Claude desktop app (also called the in-app browser, the browser pane, Claude's browser, or "your own browser"), whose tools are named mcp__Claude_Browser__* when the session runs in the desktop app and mcp__remote-devices__Claude_Browser__* when a cloud session is linked to the person's computer; before those tools are turned on there may be a single enable__mcp__remote-devices__Claude_Browser tool instead. It covers the pane's persistent sign-ins, tabs and preview_start, reading pages as text, site approvals, what the pane cannot open, and what to do when it cannot be reached. It is not for Claude in Chrome (mcp__claude-in-chrome__* tools), which has its own skill, and it does not decide which browser to use.
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。
Suite of tools for creating elaborate, multi-component claude.ai HTML artifacts using modern frontend web technologies (React, Tailwind CSS, shadcn/ui). Use for complex artifacts requiring state management, routing, or shadcn/ui components - not for simple single-file HTML/JSX artifacts.
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 the user wants intellectual understanding — learning how or why something works, not getting a task done or soliciting Claude's judgment. Trigger for: - Explicit learning requests: teach, explain, ELI5, walk me through, quiz me, flashcards, "I'm rusty on"; definitions ("what is X") - Terse concept names implying "help me understand this": "Galois theory," "transformers, from scratch" - Confusion signals: "won't stick," "keep mixing these up," "not getting it" - Learning-path questions: prerequisites, sequencing, what to study before X - Conceptual questions about mechanisms, causes, or dynamics Don't trigger for: - Tasks: coding, writing, calculation, translation, factual lookup, news updates - Personal troubleshooting; resource/textbook recommendations - Claude's evaluative verdict: opinion prompts ("do you think X", "settle this", "honest take", "is X dead / still taken seriously") and interpretive takes ("was X really as harsh as people say")
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。
Sets up, checks or changes the optional Jev judge, the TypeSafe decision model that ship-check asks about review findings (is this real harm, is a small one worth fixing now, what proof does a small fix need). Shows whether it is on for each repo, which key it uses, switches it on or off, and sends one test request. Runs only when the user types 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。
Reviews a change before it is merged, from little or no input. With nothing typed it reviews the branch you are on, uncommitted work included, against its base, its PR and its ticket, so a developer can check their own work before asking for review. With PR links, repo#N or a branch it reviews someone else's change the same way, several repos at once. It judges the failed CI checks and every Bugbot and reviewer comment, gets a fresh breaker review, traces every other piece of code that uses what changed, proves each finding or marks it unproven, says what the merge needs (a build, env vars, migrations, deploy order) and how to check the deploy, never posts to GitHub, and offers fixes only after the report. Runs only when the user types 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。
Nexscope Ozon product report search: filters Ozon products by multi-dimensional metrics including sales, revenue, sales/revenue growth rate, cart conversion rate, order conversion rate, price, rating, review count, QA count, variant count, page views, gross margin, return/cancellation rate, ad spend share, weight/volume, listing time, brand, seller, fulfillment method, and labels. Returns each product's SKU, title, price (RUB), sales, revenue, lost revenue, conversion rate, rating, reviews, brand, seller, fulfillment method, listing days/months, and complete product report fields. Use for Ozon product selection, competitor product analysis, best-seller mining, price/conversion band filtering. Trigger when the user mentions Ozon product report, Ozon product selection, Ozon product filtering, Ozon product analysis, Ozon best-selling products, Ozon competitor product analysis, Ozon product report, Ozon product screener, filter Ozon products by sales, Ozon best-seller mining, Nexscope Ozon product report. Also trigger when the intent is to filter Ozon products by multiple metrics and view product-level reports, even without explicitly mentioning Nexscope.
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。
Nexscope Ozon keyword mining: mines Ozon (and Wildberries) related keywords around a seed keyword with multi-dimensional filtering by search volume, growth, product count, seller count, competitor count, price, relevancy, title density, cart-add conversion, etc. Each mined keyword carries a full market profile (monthly search volume, growth, market space, competitor/seller counts, average price, cart-add conversion, top products). Use for Ozon keyword expansion, long-tail keyword mining, and seed keyword opportunity analysis. Trigger when the user mentions Ozon keyword mining, Ozon keyword expansion, Ozon long-tail keyword mining, find related keywords around a term, Ozon blue-ocean keyword mining, Nexscope Ozon, Ozon keyword mining, Ozon keyword expansion, Ozon related keywords, mine Ozon keywords. Also trigger when the intent is to mine Ozon related keywords around a seed term and view market profiles, even without explicitly mentioning Nexscope.
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。
Nexscope Ozon market hot keyword search: filters Ozon (and Wildberries) market keywords by multi-dimensional metrics including search volume, growth, product count, seller count, competitor count, price, sales, conversion concentration, etc. Each keyword carries monthly search volume, growth, market space, competitor/seller counts, average price, cart-add conversion, top products, and market profile. Use for Ozon keyword selection, blue-ocean keyword mining, and market opportunity analysis. Trigger when the user mentions Ozon hot keywords, Ozon keyword market analysis, Ozon keyword selection, Ozon blue-ocean keywords, Ozon search volume, Wildberries keywords, Nexscope Ozon, Ozon market keyword search, Ozon keyword research, blue ocean keywords Ozon. Also trigger when the intent is to filter Ozon market keywords by metrics and view market profiles, even without explicitly mentioning Nexscope.
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。
Nexscope Ozon keyword reverse lookup: reverse-looks up Ozon (and Wildberries) search keywords by a list of product SKUs (up to 20), returning which search terms those products appear under (organic/ad search terms), with multi-dimensional filtering by search volume, growth, product count, seller count, competitor count, natural rank, ad rank, exposure, conversion, cart-add conversion, etc. Each keyword carries monthly search volume, growth, market space, competitor/seller counts, average price, cart-add conversion, top products, and organic/ad channel, rank, exposure, and conversion (dimension) market profiles. Use for Ozon keyword reverse lookup, listing keyword optimization, competitor traffic word mining, and ad keyword analysis. Trigger when the user mentions Ozon keyword reverse lookup, Ozon reverse keyword search, Ozon SKU keyword reverse, Ozon product traffic keywords, Ozon competitor ranking keywords, Ozon organic/ad keyword reverse lookup, Nexscope Ozon, Ozon keyword back search, Ozon reverse keyword lookup, Ozon SKU keyword reverse. Also trigger when the intent is to reverse-lookup Ozon search keywords by product SKU and view market profiles, even without explicitly mentioning Nexscope.
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。
Nexscope Ozon shop product search: fetches the product list of an Ozon shop (seller) by shop ID, returning each product's 30-day sales, price, rating, weight, fulfillment method (FBO/FBS), seller type (local/cross-border), return/cancellation rate, and the shop's total 30-day sales. Use for competitor shop product analysis, shop bestseller mining, seller product structure analysis. Trigger when the user mentions Ozon shop products, Ozon seller product list, competitor shop analysis, Ozon shop bestsellers, Ozon seller analysis, Nexscope Ozon shop search, Ozon shop search, Ozon seller products, competitor shop analysis, Ozon store products. Also trigger when the intent is to view an Ozon shop/seller's products and sales data, even without explicitly mentioning Nexscope.
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。
Initiate natural language Q&A through Amazon's storefront Alexa shopping assistant to get shopping guidance answers, recommended product groups, ASIN lists, and follow-up questions. Each call supports only 1 prompt; for follow-ups, the agent must summarize context and concatenate a new question for a new request. A url can be used to supplement Amazon page context. Trigger when the user mentions Amazon Alexa, Alexa shopping assistant, Amazon smart assistant, AI shopping guide, conversational product selection, natural language shopping, Amazon chat Q&A, Amazon Alexa shopping, conversational shopping, AI shopping assistant, follow-up questions, product recommendation conversation, context follow-ups. Even if the user does not explicitly mention "Alexa", if their need is to "ask for product recommendations on Amazon using natural language", this skill should also be triggered.
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。
Search with feature attributions — return WHY each match scored where it did. Use when debugging recall quality, auditing for bias, or explaining results to a user.
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。