「questions」の検索結果

Editor role. Reads local materials, asks narrative questions, plans story arc. Outputs $DECK_DIR/deck.md as the sole content source. Use whenever the user says "outline", "plan slides", "organize materials", "structure", "table of contents", "narrative", or wants to structure content into a presentation.

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。

Produce an intensive, cited analytical report: executive summary, multi-angle findings, contrarian views, open questions, and full sources. Use only when the user needs rigorous synthesis of a complex topic (scientific, technical, policy, or market-analytical) that cannot be answered with a short search, and wants a formal written report, not a recommendation list. Do not use for product picks, top-N lists, quick lookups, or routine "find out about X" tasks. If the request does not clearly need this kind of report, do not use this skill. Do not use for a literature review over published papers. This skill collects evidence from the open web. A request for the literature on a biomedical, clinical, life-science, or other scientific topic — papers, studies, trials, preprints — belongs to firecrawl-research-papers, which queries Firecrawl's paper index (PubMed, bioRxiv, medRxiv, arXiv) instead of searching websites.

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 for guided MBSE work in MATLAB — starting a new project, resuming work mid-workflow on an existing project, or answering orientation questions about how the MBSE skills fit together. Trigger when the user says they want to create, start, or set up a new MBSE project; work on a model-based systems engineering / RFLPV project; or asks which skill covers which phase. Walks through phases one at a time — propose → approve → generate → run → confirm. Use proactively whenever someone mentions starting or continuing an MBSE 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。

Use when creating, asking, grading, or explaining multiple choice questions for MATLAB programming practice, concept checks, quizzes, or tutoring exercises.

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。

Add fast, local, typed decisions to any project with Laya, an open-source non-generative decision model (pip install laya). It classifies, routes, scores and answers yes/no questions about a piece of text, returning calibrated probabilities in roughly 20-35 ms on a laptop GPU, with no LLM call and no data leaving the machine. Use this skill whenever the user wants to classify or route text, triage tickets or emails, detect spam, phishing, toxicity or intent, put a guardrail in front of an agent or LLM, score something against a rubric, or replace an LLM-based classifier to cut latency or cost. Also use it when they mention Laya, Jev, a "System 1 model", "typed decisions" or a "decision model", even if they never name Laya.

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。

Choose and run ACU-only, adaptive PPU in-kernel timeline, or optional bounded joint analysis for a PPU kernel. Use for device-level bottleneck diagnosis, kernel-internal critical-path questions, or evidence that genuinely needs both; do not require all three modes.

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 an open-source project from What/Why perspective (not how-it's-implemented). Use when the user says "/analyze-oss", "분석해줘 이 오픈소스", "이 레포 뭐하는거야", "analyze this repo", "what does X do", "이거 왜 쓰는거야", "이 라이브러리 분석", provides a GitHub URL and wants understanding, or asks to deeply understand an OSS project's purpose, value, target users, and usage flow. Clones the repo to ~/opensource-analysis/<repo-name>/ (git pull if already exists), dispatches parallel subagents per analysis lens, then synthesizes a What/Why-focused report in chat. Supports optional user-specific follow-up questions.

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 "how does X work", code walkthroughs before changing something, and placement / ownership / layering questions ("where should this live", "which package owns this", "is this the right layer"). Explains subsystem architecture, runtime flow, onboarding mental models. Can critique architecture. Use why for motivation.

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。

Edits existing marketing copy in ordered passes (structure, claims, sentences, consistency, proof) and returns the edited text with a change log and a list of questions for the author. Flags claims that need evidence instead of inventing proof, and keeps the writer's voice. Use when someone says "edit this copy", "proofread this page", "tighten this", "polish this email", "review my landing page copy", "make this clearer", "check this before we publish", or asks for copy feedback on a page, ad, email or product description.

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 spreadsheet data, generate insights, and create visualizations. Use when a user asks to analyze data, explore a dataset, find trends, generate statistics, create charts from CSV or Excel data, summarize data, or answer questions about tabular 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。

Guides a founder from real decisions to a short set of written company values that people can act on: collects incidents, tests each candidate value, writes it as a trade-off with behaviors and a story, and wires it into hiring, feedback and promotion. Use when someone asks to "define our company values", "write a values document", "our values are generic, fix them", "turn our values into interview questions", "what should our culture be before we hire", or wants to check whether the team lives the values it has. Produces VALUES.md, an evidence log and an interview kit.

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。

World-class expertise in measuring, attributing, and optimizing AI-generated content performance. Combining data science rigor with content strategy intelligence to answer the questions traditional content analytics can't: Is AI content performing? Which AI variations convert? What's the true ROI of AI vs traditional content creation? This isn't vanity metrics for robots. This is the discipline of proving AI content drives business outcomes - and using that data to make AI content systems better, faster, and more profitable. Built on the principles of companies like Jasper, Copy.ai, and Notion who've scaled AI content operations with measurement as the foundation. Use when "ai content performance, ai content analytics, measure ai content, ai content roi, ai vs human content, ai content attribution, ai content testing, ai variation testing, ai content dashboard, ai content metrics, prompt performance, ai content conversion, ai content quality score, content velocity, ai content efficiency, ai-content, analytics, measurement, attribution, roi, ab-testing, performance, optimization, data-driven, content-analytics" mentioned.

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。

Klaviyo marketing operations and analyst expertise. Audit flows, segments, campaigns, deliverability, and revenue attribution. Use when the user asks about Klaviyo marketing strategy, email/SMS automation, customer segmentation, flow optimization, or lifecycle marketing. For API integration, SDK, webhook, or developer questions, see the klaviyo-developer 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。

Systematic research methodology for building comprehensive, current knowledge on any topic. Requires web_search tool. Use when questions require thorough investigation, recent developments post-cutoff, synthesis across multiple sources, or when Claude's knowledge may be outdated or incomplete. Triggered by "Research", "Investigate", "What's current on", "Latest info on", complex queries needing validation, or technical topics with recent changes.

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 explicitly asks to use the informed-patient skill to prepare for a medical appointment, organize symptoms before seeing a doctor, or evaluate the evidence behind a diagnosis or treatment. Do not trigger automatically from health questions or symptom mentions alone — requires an explicit request by 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。

Show the project's current state at a glance — stage, open tasks, open questions, overrides since the last checkpoint, current branch. Read-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。

Investigate an unexplained defect or unexpected behavior without changing application code. Use for root-cause diagnosis and an evidence-backed handoff, including a bounded unresolved result. Not for implementing a known fix, new features, or explanation-only questions.

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。

Assemble the governance record for a range — commits, overrides, ADRs, sprint auto-decisions, open questions, checkpoint findings — into one dated audit packet. Read-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。

Investigate an unexplained defect or unexpected behavior without changing application code. Use for root-cause diagnosis and an evidence-backed handoff, including a bounded unresolved result. Not for implementing a known fix, new features, or explanation-only questions.

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。

Restructure code without changing observable behavior: rename, extract, inline, move, deduplicate, or replace an internal implementation with an equivalent one. Prove parity through unchanged pre-existing tests. Not for new behavior, bug fixes, explanation-only questions, or committing finished work.

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。

Restructure code without changing observable behavior: rename, extract, inline, move, deduplicate, or replace an internal implementation with an equivalent one. Prove parity through unchanged pre-existing tests. Not for new behavior, bug fixes, explanation-only questions, or committing finished work.

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。

Mandatory pre-code gate and definition-of-done for ANY Odoo change (add field, override method, inherit view/xpath, OWL/JS patch, wizard, cron, controller, report, security, migration, bug fix, refactor, "optimize", "clean code", "stick to base"), Odoo 16-19. Also when the user pastes an Odoo traceback or install/upgrade error (ParseError "cannot be located in parent view", "Field ... does not exist", missing xmlid) or asks where an Odoo model, field, method, view or xmlid is defined. Run BEFORE brainstorming or planning: Odoo design questions are answered by tracing the real source into a Context Brief (file:line), not by open-ended Q&A or memory. Resolves the Odoo runtime and version, loads the matching odoo-<major> pack, and closes with install, test, upgrade, i18n, security and hygiene checks before commit.

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。

Route HugeGraph MCP structured graph query tasks to stable read-only tools. Use when the user asks graph questions, asks to generate Gremlin, provides Gremlin to explain, or needs read-only graph exploration.

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。

Watch a video from YouTube, Instagram, X/Twitter, Vimeo, TikTok or any of ~1800 yt-dlp sites (or a local path). Downloads with yt-dlp, extracts auto-scaled frames with ffmpeg, pulls the transcript from captions (or local mlx-whisper fallback, no API key), and hands the result to Claude so it can answer questions about what's in the 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。