「research」の検索結果

Use when designing, reviewing, implementing, or validating UI/UX and frontend experiences for web, mobile, responsive apps, design systems, Figma-to-code handoff, frontend stack/library selection, personas, UX mapping, information architecture, UI patterns, accessibility, interaction design, UX research, usability testing, theme/token application, or XR/spatial interfaces.

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。

調査・スパイクを「問いに答える」でなく「判断の危険を潰す」ために走り切る。何を決めるための調査かを計画として出して依頼者と合意し、裏付け一つで閉じず反証で開き、結論から読める形で報告するまでを担う。次の判断・見積もりが決められず調べる必要があるとき、使い捨ての実験で確かめたいときに使う。

事業仮説を支える一次/二次情報を整理し、意思決定に足る「根拠」「不確実性」「次の調査」を可視化する。でたらめな引用や推測の断言を避け、出典の実在を重視する。

Record the statements a journal requires and a reader checks — authors with their CRediT contributions, ethics approval that names the body and the reference number, how consent was taken, funding with grant numbers, conflicts of interest, data availability with an address or a reason, and the use of generative AI — as a validated record that the submission folder prints and the manuscript never carries. Use when a run is heading for submission, when an author asks who should be listed, when consent, approval or data sharing has to be stated, or when the venue's AI policy comes up.

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。

Compile deep repository evidence into artifact-bound correctness doctrine — authority/law/proof maps, owned invariants, failure archaeology, and the strongest durable destination for each piece of knowledge, plus an optional minimal repository-specific skill portfolio. Use when the user wants both deep codebase understanding AND durable doctrine, knowledge routing, or repo-specific skill recommendations. Research discoverable facts before asking. Read-only. Not for quick onboarding, one isolated invariant, ordinary implementation, generic review, or direct skill creation.

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。

Product-discovery coach for Fishbowl engineers — inspired by Marty Cagan's work (never impersonates him). Stage-routes between opportunity brief, research, PRD, ticket drafting, and outcome review. Triggers on "product coach", "help me with product", "I need to write a PRD", "I want to do discovery", "opportunity assessment", "who is this for", "why are we building this", or when an engineer is starting, resuming, or post-mortem-ing product-adjacent work. Invoke with a short description of what you want to do, or invoke bare to be surveyed and routed.

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。

Conduct a Marty-Cagan-style opportunity assessment interview and produce a ~2-page Opportunity Brief in Confluence. Covers business objective, customer, problem, success metric, current alternatives, assumptions/risks, and what we don't know yet. Triggers on "opportunity brief", "opportunity assessment", "discovery brief", "who is this for", "why are we building this", "validate this idea", "product discovery", or any request to frame a feature before implementation. One question at a time. Records accepted research gaps as structured Confluence Decision pages with bidirectional links.

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。

Mine a codebase for breakthrough, evidence-backed opportunities — features, additions, refactors, simplifications, DX, UX, reliability, performance, or architecture cleanup. Researches project reality first, then forces two escalation gates (reject the merely-adequate idea; expand ambition 10x then collapse to the smallest proof-bearing artifact). Outputs ranked opportunities, an escalation ledger, and one plan seed. Does not implement or create tickets.

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。

Clarify ambiguous or conflicting requests by researching first, then asking only judgment calls. Use when prompts say "grill me", ask hard questions, request relentless interrogation, pressure-test assumptions, clarify scope/requirements, define success criteria, or request system-design/optimization decisions before implementation; stop before implementation.

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。

Review or update stable, canonical, any-human, PMF, and adoption claims using adoption/canonicity governance packets.

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。

Load before external product/design research, competitor comparison, clean-room implementation, or adding/updating code, packages, images, fonts, datasets, generated artifacts, or other dependencies whose source/provenance/license may affect outbound licensing; not for purely internal source use with no dependency change.

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。

Comprehensive results analysis for empirical research: generate publication-quality descriptive statistics and balance tables, interpret regression coefficients with economic magnitude and effect sizes, assess identification assumption diagnostics, and produce structured results memos. Use when asked to create summary statistics, Table 1, balance tests, interpret results, assess economic significance, or write results narratives.

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。

End-to-end data pipeline for empirical research: fetch economic data from APIs (FRED, World Bank, IMF, BLS, OECD, Yahoo Finance), clean and transform raw data, construct strategy-specific variables, and validate panel structure. Use when asked to fetch data, download data, clean data, merge datasets, prepare analysis-ready 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。

Search, summarize, and synthesize economics literature. find research gaps, position your contribution.

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。

Knowledge pack from 'Towards Digital Engineering: The Advent of Digital Systems Engineering' (Huang et al., Old Dominion University, arXiv:2002.11672, 2020). Use when reasoning about digital engineering, the DoD Digital Engineering Strategy and its five goals, the Authoritative Source of Truth, digitalization vs. digitization, digital augmentation, digitalized models, provenance, unique identification, and the four-level (vision/strategy/action/foundation) DSE research framework. Covers the conceptual/vision layer of the field. SCOPE LIMITS: this is a single ~28-page vision paper, not a methods handbook — it is thin on step-by-step procedures, tooling, case studies, and quantitative evaluation, and it predates 2020 so it does not cover later digital-engineering standards or recent AI/LLM advances. Use the sebok pack for established SE canon and MBSE depth.

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 video transcripts (subtitles) and metadata from online video sources and output them as Markdown, JSON, or plain text. Currently supported: YouTube. Prefers manually created subtitles, falls back to auto-generated ones.

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。

Router and protocol for reading and extracting web content. Decides first WHAT is needed (main text vs. structure vs. screenshot) and then WHICH tool available on the system delivers it. If nothing suitable is present, it recommends installing the web-scraper module.

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。

Manages your own skill landscape: surveys and compares existing skills (Audit mode), researches the web for new skills/plugins (Explore mode), and is at the same time the installer that generates lean subskills (Skill-Finder, family umbrella, maintenance skills) instead of loading a monolith. Use this skill for "compare/audit skills", "which skills are duplicated", "form skill families", "clean up/consolidate skills", "maintain the skill register", "find skills/plugins for topic X", "install new skills", "browse the skill marketplace", or for `/skill-explorer`. Delivers a sub-report per family and a globally numbered decision list; installs/uninstalls only after a security check and explicit approval.

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。

Structured 6-step procedure for improving, renovating, or rebuilding existing pipelines, individual project folders, documentation structures, or software stacks. Addressable as "pipeline optimizer" (for whole topic pipelines, e.g. a software, research, or game-dev pipeline) or "project-folder optimizer" (for individual project folders within a pipeline, e.g. a single software tool or paper project). Triggers on tasks like "improve pipeline X", "optimize the stack", "rebuild Y", "renovation", "pipeline refactoring", "clean up project folder", "improve folder structure", "unify conventions", "documentation consolidation", "integrate into existing system", or any substantial intervention in established structures. Delivers building-stock analysis, purpose clarification, ideal sketch, gap plan, empirical pain-point identification, and retests with fresh subagents. Prevents parallel standards, duplication, and pipeline breaks.

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。

Prepares a DRAFT vendor risk screening brief from the material the user provides on one vendor (questionnaire answers, certificates, assurance reports, policies, contract extracts): per screening topic, what a document evidences with reference, date and scope, what is only asserted, what is missing or contradicted, certificate and report details as stated, and ready-to-send questions for the vendor and the internal owners. No web research, no risk rating, tier, score or recommendation. Use when the user asks to "screen this vendor", "review the vendor's questionnaire answers", "check what the vendor's certificate covers", "what is missing from this due diligence pack" or "draft the follow-up questions for the vendor". Do not use for answering a customer's questionnaire about your own organisation, use vendor-security-questionnaire-prefill instead. Drafts for human review; never approves, authorises or signs 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。

Builds one DRAFT message house for a product, service, programme or initiative from the source material the user provides: an umbrella statement, two to four pillars and graded proof points under each, with every proof point that lacks a source flagged, a claim sensitivity table, an audience coverage check and open questions. Use when the user asks to "build a message house", "write our messaging framework", "what are the key messages for this launch", "turn this research into messaging pillars" or "test our current messaging against the evidence". Do not use for a campaign one-pager, use campaign-brief-builder instead; to check whether a written document's claims are substantiated, use claims-evidence-map. Drafts for human review; never approves, authorises or signs 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。

Recall past work across Claude Code and Codex sessions. Finds decisions, research, fixes, and conversations by intent; with only a project and no question, orients on that project's recent state.

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。

特定の日本株1銘柄について、企業概要・セグメント経済性・財務トレンド・株主構成・ガバナンス・リスク要因・競争優位の仮説・バリュエーション素材までを網羅した総合リサーチレポートを作る時に使う。「トヨタを分析して」「〇〇の株を調べて」のように1社を深掘りする指示で発火する。

- Research companies, directors, shareholders and ultimate beneficial ownership in official corporate registries, filings and offshore datasets — OpenCorporates, UK Companies House and the PSC register, SEC EDGAR, US Secretary of State registries, EU business registers, GLEIF LEI… Use when asked who owns or controls a company, to find a person's other directorships, or to unpick a group structure

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。