2,221 件 ・ 関連度順
概要と使いどころ
对比图/一图流：生成 A vs B 参数对比图、优劣势对比表、产品参数一图流。 用 HTML+CSS 渲染成可截图的视觉卡片，适合小红书/微博等平台分享。 使用时机：用户说"做个对比图"、"A vs B"、"参数对比"、"优劣对比"、 "一图流"、"对比表"、"哪个好"、"对比一下"。 和 chart-visualization 的区别：chart 做数据图表（柱状图/折线图），comparison-card 做对比表/一图流。 和 infographic 的区别：infographic 做多维信息图，comparison-card 专注 A vs B 对比。
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。
Convert raw notes, error logs, voice dictation, or screenshots into crisp GitHub-flavored markdown issue reports. Use when the user pastes bug info, error messages, or informal descriptions and wants a structured GitHub issue. Supports images/GIFs for visual evidence.
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。
Perform finance web searches and local context searches. Use when the user needs general finance info from the web (Jina/DDG/Baidu) or needs to retrieve finance information from a local document store (RAG).
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 Node.js project's installed npm dependency tree for known CVEs by wrapping the npm audit JSON output and emitting findings in the canonical penetration-tester schema. Detects direct AND transitive vulnerabilities, normalizes npm's severity scale (info/low/moderate/ high/critical) to the shared Severity enum, and parses both v1 and v2 audit output formats so the skill works against npm 6 and npm 7+ lockfiles. Use when: pre-merge gate on a Node project, post-incident sweep after a transitive package compromise (e.g. event-stream, ua-parser, node-ipc, color.js), SOC2 vendor-management evidence collection, or auditing an inherited or acquired Node codebase. Threshold: any HIGH or CRITICAL CVE in the resolved dependency tree. MODERATE / LOW reported informationally. Trigger with: "audit npm deps", "npm vulnerability scan", "check node packages for CVEs", "npm 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。
Collect Apollo.io debug evidence for support. Use when preparing support tickets, documenting issues, or gathering diagnostic information for Apollo problems. Trigger with phrases like "apollo debug", "apollo support bundle", "collect apollo diagnostics", "apollo troubleshooting info".
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 software complexity through deep modules, information hiding, and strategic programming. Use when the user mentions "module design", "API too complex", "shallow class", "complexity budget", "strategic vs tactical", "deep module", "information leakage", "pass-through method", "this code is over-engineered", or "simplify this design". Also trigger when reviewing an interface for simplicity, evaluating whether an abstraction is pulling its weight, deciding whether a comment is worth writing, or choosing between general-purpose and special-purpose approaches. Covers deep vs shallow modules, red flags for complexity, and comments as design documentation. For code quality, see clean-code. For architecture boundaries, see clean-architecture.
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 and directs the visual assets that carry content — carousels, infographics, quote graphics, diagrams, and social imagery — including the generation prompts where they are AI-produced. Use this to turn a written piece into a visual format, design a carousel or infographic, create social graphics, or fix visuals that are not stopping the scroll.
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 complete cross-disease shared-biomarker bioinformatics research designs from a user-provided disease pair and validation direction. Always use this skill whenever a user wants to design, plan, or build a multi-dataset study linking two related diseases through shared DEGs, enrichment, PPI hub genes, public validation, regulatory-network analysis, immune infiltration, drug-gene interaction screening, and optional qRT-PCR or cell-line validation. Covers five study patterns (shared-DEG discovery, hub-gene prioritization, regulatory-network interpretation, immune/drug follow-up, bioinformatics-plus-validation) and always outputs four workload configs (Lite / Standard / Advanced / Publication+) with recommended primary plan, step-by-step workflow, figure plan, validation strategy, minimal executable version, publication upgrade path, and a strictly verified reference literature retrieval layer with real references only.
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。
A medical-research-native literature reading skill for users with clinical, bioinformatics, translational, and basic experimental backgrounds. Use this skill whenever a user wants to read, analyze, critique, or interpret a medical or scientific paper — whether they provide a PDF, abstract, DOI, PMID, or just a title. Triggers include requests like \"analyze this paper\", \"critique this study\", \"is this a strong paper?\", \"give me similar studies\", \"prepare me for journal club\", \"help me understand this bioinformatics paper\", \"what are the weaknesses here?\", or \"turn this into a mind map\". Also activate for any downstream deliverables such as journal club kits, comparison tables, PI decision briefs, replication starters, or follow-up experiment designs. Do NOT treat as a generic summarizer — this skill performs structured evidence-type classification, track-specific critical appraisal, interpretation-boundary judgment, and research-grade follow-up generation.
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 asks what information a Stripe Connect connected account must provide for verification, onboarding, KYC, or account requirements; when they need to compare requirements between connected-account setups; or when they ask which verification fields, documents, or business details are required for a particular platform country, account country, business type, dashboard, service agreement, or capability.
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 media file properties - duration, resolution, bitrate, codecs, and stream information
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 includes search capability in 13F, such as fuzzy search a fund information using possibly inaccurate name, or fuzzy search a stock cusip info using its name.
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。
Diagnostic guide for RL-based post-training of language models (GRPO, PPO, REINFORCE, DPO). Use proactively when debugging a training pipeline that shows no improvement, loss anomalies, reward stagnation, NaN gradients, or other unexpected behavior during reinforcement learning fine-tuning. Work through all pipeline stages — reward, advantages, log-probs, loss, generation/decoding — before concluding the diagnosis is complete; stopping after one or two fixes is a common failure mode. Covers log-probability math, advantage estimation, numerical stability, reward processing, and generation/decoding pipeline issues.
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 computing 3D step-response performance metrics for point-to-point drone flight — rise time, settling time, percent overshoot, and steady-state error based on Euclidean distance to the final target. Use instead of 1D stepinfo for any flight where all three position axes move simultaneously.
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。
Verifies factual claims in documents using web search and official sources, then proposes corrections with user confirmation. Use when the user asks to fact-check, verify information, validate claims, check accuracy, or update outdated information in documents. Supports AI model specs, technical documentation, statistics, and general factual statements.
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。
Answer a construction request for information so the site can act on it — a direct answer, the drawing or specification reference that supports it, and an explicit statement of whether it changes cost or programme. Use when asked to respond to an RFI, answer a contractor query, or handle a request for information on site, or when RFIs keep coming back for clarification. Produces the answer with its reference, the cost and time implication stated, the instruction status, the distribution list, and the register entry.
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 asked 个人信息保护影响评估怎么做, 写一份 PIA, 处理敏感个人信息要评估吗, 自动化决策评估, PIPL 第五十五条, or assess a processing activity under China's Personal Information Protection Law. Produces a personal information protection impact assessment (个人信息保护影响评估) covering the PIPL Article 55 triggers, the Article 56 questions (lawful, legitimate and necessary; impact and risk; adequacy of protection), a risk register with mitigations and owners, and a record kept for at least three years.
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 asked 数据出境要申报吗, 数据出境安全评估还是标准合同, 个人信息出境标准合同怎么备案, 我们把数据传到海外总部合规吗, or decide how to transfer data out of mainland China lawfully. Produces a data map of what leaves China, the route that applies (an exemption, the personal information export standard contract, certification, or a CAC security assessment) with the thresholds to confirm, the filing steps, and the documents to prepare, including the personal information protection impact assessment.
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。
AI image generation for SEO assets: OG/social preview images, blog hero images, schema images, product photography, infographics. Powered by Gemini via nanobanana-mcp. Requires banana extension installed. Use when user says "generate image", "OG image", "social preview", "hero image", "blog image", "product photo", "infographic", "seo image", "create visual", "image-gen", "favicon", "schema image", "pinterest pin", "generate visual", "banner", or "thumbnail".
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 partitioning content between an Advanced Materials main text and its Supporting Information, ensuring the paper stands alone while extended data, full experimental detail, and secondary characterization live in the SI. Organizes the Supporting Information; does not write the main text.
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 mechanism analysis for a 《会计研究》 (Accounting Research) manuscript is missing or mis-specified — the channel must be an information mechanism (reduce information asymmetry, raise disclosure quality, constrain earnings management, improve audit assurance), not a generic pricing or financing channel. Use after the main result holds.
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。
Look up information about a person - work history, social profiles, contact info
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 asks what information a Stripe Connect connected account must provide for verification, onboarding, KYC, or account requirements; when they need to compare requirements between connected-account setups; or when they ask which verification fields, documents, or business details are required for a particular platform country, account country, business type, dashboard, service agreement, or capability.
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 importing or exporting vehicle data from/to log files (MDF/MF4/DAT, BLF, ASC/TXT), decoding CAN/CAN FD/LIN messages to signals via DBC, ARXML, or LDF databases, writing timetable data to MDF or BLF files, or calling blfread, blfinfo, blfwrite, mdfRead, mdfWrite, mdfCreate, mdfInfo, canSignalImport, canMessageImport, canMessageTimetable, canFDMessageTimetable, canSignalTimetable, or linMessageTimetable.
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。