「questions」の検索結果

Interactive setup wizard that configures a new project for the social-science-research plugin. Asks the user questions about their field, institution, journals, datasets, key researchers, and R color palette, then writes the answers into references/domain-profile.md and CLAUDE.md. Make sure to use this skill first whenever a user is starting fresh or wants to configure the plugin. Triggers include: "set up my project", "configure the plugin", "run setup", "initialize this project", "I just installed the plugin", "set my field", "set my institution", "configure my domain profile", or any request to personalize the plugin for a specific research context.

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Main orchestration workflow for systematic literature research - search, evaluate, traverse, synthesize

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Conduct rigorous thematic analysis (TA) of qualitative data following Braun and Clarke's (2006) six-phase framework. Use whenever the user mentions 'thematic analysis', 'TA', 'Braun and Clarke', 'qualitative coding', 'identifying themes', or asks for help analysing interviews, focus groups, open-ended survey responses, or transcripts to identify patterns. Also trigger for questions about inductive vs theoretical coding, semantic vs latent themes, essentialist vs constructionist epistemology, building a thematic map, or writing up a qualitative findings section. Covers all six phases, the four upfront analytic decisions, the 15-point quality checklist, and the five common pitfalls. Produces a Word document write-up and an annotated thematic map. Does NOT cover IPA, grounded theory, discourse analysis, conversation analysis, or narrative analysis — use a different method for those.

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STATA code pattern library for empirical archival accounting research. Provides tested syntax from 126 peer-reviewed JAR (Journal of Accounting Research) replication files (2017-2025). Use when the user asks procedural questions like "How do I implement [method]?" or "Show me code for [technique]" — including: entropy balancing, propensity score matching (PSM), difference-in-differences (DiD), regression discontinuity (RDD), instrumental variables (IV), event studies (CAR/BHAR), survival analysis, Fama-MacBeth regressions, bootstrap, quantile regression, reghdfe/xtreg/areg, clustering standard errors, fixed effects, esttab/outreg2 table formatting, winsorization, leads/lags. Users can specify their variables (e.g., treatment, outcomes, controls) and receive adapted syntax. NOTE: This skill provides code patterns from published papers, not research design advice.

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 ordinary text plans into rich interactive visual plans with diagrams, file maps, annotated code, open questions, and UI/prototype review when useful.

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 wants autonomous progress without routine clarification stops: "plow ahead", "do not stop", "use your best judgment", "keep going until done", "finish while I am away", "do not ask questions unless truly blocked", or similar. Convert ordinary ambiguity into stated assumptions, proceed through implementation and validation, stop only for true blockers, and end with a clear recap of decisions, changes, verification, and residual risk.

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Scope a feature end to end and write an implementation spec under specs/ from an accepted proposal — current-system mapping, goals/non-goals, a Decision Log for one-way-door choices, a live Open Questions backlog, and a real migration + test plan. Read when asked to write a spec, scope this feature, turn this proposal into a spec, plan the implementation, or break this into tasks. Do NOT fire on frame a proposal or write the PRD (sibling frame-a-proposal — a PRD frames a change before it is accepted; this skill starts once one is), record a decision or write the ADR (record-a-decision), write a postmortem (write-a-postmortem), or review this design (review-a-design) — those are separate skills. Complements the platform open-knowledge skill; does not replace it.

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Frame a new design proposal (RFC-shape) under proposals/ — problem before solution, named beneficiary and observable change, real alternatives, honest drawbacks, and a live open-questions backlog. Read when asked to frame a proposal, write an RFC, propose a design, pitch a change, draft a PRD-style design doc, or open a design proposal for review. Do NOT read to record a decision after it is accepted (use record-a-decision), to write an implementation spec (use write-a-spec), to write a postmortem (use write-a-postmortem), or to review or critique an existing design (use review-a-design).

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。

Find the exact pages AI assistants cite when answering questions in your category, and identify which ones you can get into. Claude clusters the cited sources, scores each by attainability, and outputs an outreach/content plan. Platform: AI visibility.

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Examine what a file claims about itself and what it actually contains — powered by Apache Tika. True content-based type detection (extensions lie), provenance claims (authors, dates, creating application), revision and tamper signals (PDF incremental updates, tracked changes, hidden slides, zip integrity), hidden and embedded content (attachments, macros), risk indicators (PDF JavaScript actions, encryption), and content digests. Evidence gathering, not verdicts: Tika reports what the file asserts and what parsing observed; it does not attribute authorship or validate signatures. Use for triaging suspicious files, provenance questions, e-discovery-style review, or "is this file what it claims to be."

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。

Inspect and profile React Native component trees from agent-device. Use for React Native performance, profiling, props, state, hooks, render causes, slow components, excessive rerenders, or questions like why a component rerendered.

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 starting any conversation - establishes how to find and use skills, requiring skill invocation before ANY response including clarifying 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。

Maps questions to the optimal tldr command. Use this to pick the right 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。

Coordinate safe, evidence-based paid-media work across Google Ads, Meta Ads, X Ads, LinkedIn Ads, Reddit Ads, TikTok Ads, Amazon, and ChatGPT Ads. Use for broad ads questions, multi-channel strategy, budgets, CPA or ROAS, campaign requests, spend, ad performance, or when routing to the right NotFair paid-ads skill.

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Cross-model second opinion from Google Gemini — a different AI reviewing the same changes, with deep Google ecosystem knowledge. Three modes: review (pass/fail gate for Google Ads campaigns, SEO metadata, or code), challenge (adversarial stress-test that tries to break your changes), and consult (open Q&A with Gemini on Google Ads strategy, SEO best practices, or implementation questions). Use when the user says "gemini review", "ask gemini", "gemini challenge", "second opinion from gemini", "consult gemini", "stress test with gemini", "what would gemini say", "cross-model review", or "get another opinion". Voice aliases: "gem", "gemini check". Especially useful for Google Ads changes, SEO metadata updates, campaign structure decisions, keyword strategies, and bid/budget changes — Gemini has native Google ecosystem knowledge that complements Claude's 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。

Explain NotFair's paid-ads skills, installation, platform boundaries, account connections, and current product capabilities. Use for questions about how NotFair works, what it supports, how to install or connect it, plans or limits, or paid-media troubleshooting that is not an account-performance 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。

实践认识论：把方案、假说或判断放回实践中检验，按「实践 → 认识 → 再实践」螺旋迭代，并在开始前写明循环终止条件。当你提出了假说要验证、一次尝试失败要复盘再来、发现自己只想不做或只做不想时触发；一次性输出、答案可直接查阅、还没形成假说（先调查）时不触发。 English: Practice-cognition loop. Test a hypothesis or plan in practice, learn from the result, and iterate in a rising spiral with an explicit stop condition. Trigger when a plan needs validation, an attempt failed and must be retried, or you notice thinking without doing (or doing without thinking); skip for one-shot outputs, lookup questions, or before any hypothesis exists.

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。

Handles git work: atomic commits, rebase, squash, blame, bisect, reflog, and history questions. Use whenever a task needs a commit or a git-history investigation; skip for ordinary code edits.

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Analyze git repositories to build a security ownership topology (people-to-file), compute bus factor and sensitive-code ownership, and export CSV/JSON for graph databases and visualization. Trigger only when the user explicitly wants a security-oriented ownership or bus-factor analysis grounded in git history (for example: orphaned sensitive code, security maintainers, CODEOWNERS reality checks for risk, sensitive hotspots, or ownership clusters). Do not trigger for general maintainer lists or non-security ownership 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 when the user wants to mine comments and replies for audience reactions, customer language, questions, objections, complaints, product ideas, buying intent, sentiment, or voice-of-customer insights from public social posts and videos.

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Gather phase context through adaptive questioning before planning. Use --all to skip area selection and discuss all gray areas interactively. Use --auto to skip interactive questions (Claude picks recommended defaults). Use --chain for interactive discuss followed by automatic plan+execute. Use --power for bulk question generation into a file-based UI (answer at your own pace).

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。

Answers questions about a past agent run from its recording rather than from memory, and replays or forks that run. Use when asked why an earlier run did something, or to reproduce a 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。

Look up official macroeconomic releases, central-bank policy rates, release calendars and FX rates for 22 currencies through the FXMacroData MCP server. Use for questions about CPI, GDP, jobs data, rate decisions, bond yields or what data is due next, when the answer should come from the published number rather than news coverage. Remote server at https://mcp.fxmacrodata.com/mcp; USD works without a key.

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。

Fetch a real product's current price, stock, rating, or images from retailer pages over the Apify MCP server, and return them as typed fields rather than prose. Use when someone asks what a product costs right now, whether it is in stock, how it is rated, to compare a product across retailers, or to check a product URL they pasted. Also use when an agent would otherwise answer a product question from training data. Not for managing your own store's catalog, not for payments, and not for questions answerable without live retailer 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。