「rce」の検索結果

Assemble product footage, UGC, and b-roll into a conversion-oriented montage with a hook → pain → demo → proof → CTA rhythm. Use for 带货混剪, 产品混剪, 商品短视频, 种草视频, ecommerce montage, product reel, UGC cutdown, or when the user wants selling footage cut into a short that converts.

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 what people are actually saying about a topic in the last 30 days across Reddit, X / Twitter, YouTube, Hacker News, dev.to, Medium, and other public discourse platforms. API-free; uses WebSearch with platform-targeted site operators plus recency filters. Produces DISCOURSE.md (a structured brief) and JSON output the writer can consume. Complements blog-researcher (which focuses on authority sources) with a recency-and-engagement lens. Not for verifying statistics (blog-factcheck) or gathering authority sources. Use when user says "blog discourse", "discourse research", "what are people saying about", "research what people are saying", "voice of customer", "social listening", "30-day research", "trend research", "what's the discussion on", "real-time research", "practitioner discourse", "/blog discourse".

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 dark-mode-compatible inline SVG data visualization charts for blog posts. Supports horizontal bar, grouped bar, donut, line, lollipop, area, and radar charts with automatic platform detection (HTML vs JSX/MDX). Enforces chart type diversity, accessible markup (role=img, aria-labelledby), source attribution, and transparent backgrounds. Use whenever the user mentions data visualization, charts, graphs, comparison tables that need to be visualized, or wants to embed inline SVG visualizations in a blog post, even if not invoking blog-write. Use when user says "blog chart", "generate chart", "data visualization", "svg chart", "blog graph", "visualize data", or when the blog-write workflow identifies chart-worthy data points (3+ comparable metrics, trends, before/after data).

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。

Scaffold and operate Claude Blog Brain, a source-cited Obsidian brain for blog content creation, optimization, and management dual-optimized for Google rankings (E-E-A-T, the 2026 core updates) and AI citations (GEO/AEO), spanning writing, rewriting and freshness, SERP-informed briefs and outlines, editorial calendars and strategy, semantic topic clusters, schema and internal linking, multilingual publishing, the FLOW framework, factchecking, personas, distribution, and the blog delivery contract, grounded in the claude-blog skill. Use when the user says "claude-blog-brain", "Claude Blog Brain", "create a blog content creation, optimization, and management dual-optimized for Google rankings (E-E-A-T, the 2026 core updates) and AI citations (GEO/AEO), spanning writing, rewriting and freshness, SERP-informed briefs and outlines, editorial calendars and strategy, semantic topic clusters, schema and internal linking, multilingual publishing, the FLOW framework, factchecking, personas, distribution, and the blog delivery contract, grounded in the claude-blog skill brain", "import sources", "synthesize plan", "render report", or wants a persistent vault-backed operating system for blog content creation, optimization, and management dual-optimized for Google rankings (E-E-A-T, the 2026 core updates) and AI citations (GEO/AEO), spanning writing, rewriting and freshness, SERP-informed briefs and outlines, editorial calendars and strategy, semantic topic clusters, schema and internal linking, multilingual publishing, the FLOW framework, factchecking, personas, distribution, and the blog delivery contract, grounded in the claude-blog 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。

Discuss a domain with the user, research it from real sources, then generate a trusted skill bundle for it - a step-by-step workflow with a flowchart, a domain adapter, a trap fixture, and a smoke eval. Use when the user says "/fable-domain SECTOR", "make a skill for DOMAIN", "add a domain to the fable method", or "give a lesser model Fable's workflow for DOMAIN". The bundle is the deliverable; a workflow without its flowchart, sources, and trap is not 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。

Use with the dstack skill for model-serving work when the image, serving command, resources, backend/fleet choice, or service behavior is not proven. Guides task-first prototyping on real hardware, choosing fleets/backends that can reuse idle instances and caches, checking vLLM/SGLang sources, and verifying the final dstack service with a model request.

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。

Manage Model Context Protocol (MCP) servers - discover, analyze, and execute tools/prompts/resources from configured MCP servers. Use when working with MCP integrations, need to discover available MCP capabilities, filter MCP tools for specific tasks, execute MCP tools programmatically, access MCP prompts/resources, or implement MCP client functionality. Supports intelligent tool selection, multi-server management, and context-efficient capability discovery.

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 external compatibility between two DSH (DeepSeek Harness) versions and detect reverts, producing an upgrade-report directory; compares git tags with a source checkout, or published npm packages without one. Use whenever the user asks to check/compare/audit two DSH versions or whether upgrading is safe — e.g. "more changes or reverts in dsh-vX -> dsh-vY", "compare the breaking changes" — even with only two version numbers and no source location. Read-only outside the report directory; npm mode installs in isolation with --ignore-scripts.

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 for DSH plugin compatibility, migration, upgrade, regression, or post-upgrade diagnosis, including read-only review of already-migrated plugin source and version-boundary, API, dependency, activation, or runtime compatibility problems. Inspection and diagnosis stay read-only; show a plan and obtain confirmation before any configuration, dependency, or source 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。

Build MCP (Model Context Protocol) servers using the official @modelcontextprotocol/sdk. Use this skill when users ask to create an MCP server, MCP tools, MCP resources, or want to expose APIs/functionality to AI agents. This skill covers vanilla MCP implementation with Streamable HTTP transport, session management, tools, resources, and prompts.

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。

Builds and interrogates a project schedule — logic-driven sequencing, dependency types and lags, float and the critical path, resource loading and leveling, schedule risk analysis, and measuring progress against a baseline rather than against optimism. Use this to construct a schedule, audit one you have inherited, find out why a plan keeps slipping, work out what a date change actually costs, or judge whether a reported percentage complete means anything.

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。

Plans the shape and size of the workforce — demand for roles, build-versus-buy, attrition, and sequencing hiring against budget. Use this to build a hiring plan, decide which roles to open and in what order, model attrition and backfill, plan for a growth or contraction scenario, or connect headcount plans to the budget.

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。

Governs the portfolio of work — intake, prioritization, stage gates, resource contention, and stopping things. Use this to set up intake and prioritization, run a stage gate, decide between competing initiatives, resolve resource contention across projects, or work out why everything is in flight and nothing is finishing.

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。

Designs the warehouse and semantic layer — source-to-mart structure, dimensional modeling, grain, slowly changing dimensions, and the metric layer analytics reads through. Use this to design or restructure a warehouse, model a new source, decide on grain or table structure, build a semantic or metric layer, or diagnose why queries are slow, wrong, or impossible to 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。

WeCom (Enterprise WeChat) CLI - official open-source CLI tool from WeCom. Covers 7 business categories: Contacts, Todos, Meetings, Messages, Schedules, Documents, Smartsheets. Built in Rust for macOS/Linux/Windows. Use when user wants to operate WeCom 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。

Feishu/Lark CLI - official open-source CLI tool from Feishu for AI Agents. Provides 200+ commands across 12 business domains: IM, Docs, Sheets, Base (Bitable), Calendar, Video Meeting, Mail, Tasks, Wiki, Drive, Contacts, Search. Supports both user identity and bot identity authentication. Use when user wants to operate Feishu/Lark 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。

DingTalk Workspace CLI (dws) - officially open-sourced cross-platform CLI tool from DingTalk. Provides 86 commands across 12 products: Contact, Chat, Bot, Calendar, Todo, Approval, Attendance, Ding, Report, AITable, Workbench, DevDoc. Built in Go with zero-trust security architecture. Use when user wants to operate DingTalk 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。

Baidu E-commerce skill for cross-platform price comparison, review analysis, and purchase knowledge. Complete workflow from product discovery to purchase decision. Use when user wants to compare prices, read reviews, or make purchase decisions.

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。

Make the build step a real gate on what you actually distribute — build scripts that warn and exit 0 on a missing input, size checks with only an upper bound, hand-maintained file lists that drift from the entrypoints they must cover, committed bundles that go stale when only the source changes, GNU-only shell in release scripts that aborts on the other OS, and verification that runs against the source tree instead of the artifact. Use when writing or reviewing a build/package script, a `dist/` copy step, a release workflow that uploads a zip or installer, or a committed compiled asset.

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。

Designs complete single-cell research plans from a user-provided biomedical direction. Always use this skill whenever a user wants to design, scope, or structure a single-cell study — including disease-focused, mechanism-focused, biomarker-focused, translational, perturbation-inspired, or validation-aware projects. It should define the research question, choose the best-fit study pattern, recommend sample grouping logic, suggest reference datasets as examples only, specify the core analysis modules, propose a validation ladder, and output four workload configurations (Lite / Standard / Advanced / Publication+). Never fabricate datasets, sample metadata, accession numbers, cohort availability, cell-type labels, external validation resources, or literature references. Always include the mandatory Dataset Disclaimer immediately before any workflow section that mentions datasets or public 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。

Designs QTL colocalization studies that connect eQTL, pQTL, sQTL, or related molecular QTL signals with GWAS loci. Always use this skill whenever a user wants to plan, scope, or structure a locus-level study asking whether a GWAS association and a molecular QTL association may reflect the same underlying causal signal. Covers locus definition, QTL/GWAS source architecture, ancestry and LD alignment, single-locus vs multi-locus strategy, candidate-gene prioritization, optional fine-mapping, linked MR/SMR follow-up, and functional annotation. Always output four workload configurations (Lite / Standard / Advanced / Publication+) with a recommended primary plan, stepwise workflow, method rationale, evidence hierarchy, figure plan, minimal executable version, and strictly verified literature guidance with no fabricated references. Never equate colocalization with causality proof, mediation proof, or automatic target validation. Always include the mandatory Dataset Disclaimer immediately before any workflow section that mentions datasets, repositories, consortia, or public 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。

Assesses whether a medical research topic is worth starting now by separating true novelty from pseudo-novelty, auditing real feasibility under stated resource constraints, and forcing a concrete start / narrow / redesign / stop decision. Always require explicit assumptions and never fabricate references, datasets, resource availability, precedent studies, or publication claims.

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。

React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.

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。

Local drop-in API emulator for Vercel, GitHub, Google, Slack, Apple, Microsoft, AWS, Clerk, Linear, Twilio, and other developer APIs. Use when the user needs to start emulated services, configure seed data, write tests against local APIs, set up CI without network access, or work with the emulate CLI or programmatic API. Triggers include "start the emulator", "emulate services", "mock API locally", "create emulator config", "test against local API", "npx emulate", or any task requiring local service emulation.

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。