調査、論文、教育、資格学習（4,125 件）
概要と使いどころ
Use this skill to query your Google NotebookLM notebooks directly from Claude Code for source-grounded, citation-backed answers from Gemini. Browser automation, library management, persistent auth. Drastically reduced hallucinations through document-only responses.
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。
Handle tool failures when researching regulatory/government content by using fallback methods and domain knowledge
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。
Fallback workflow for regulatory research when web extraction tools fail on government PDFs
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。
Handle web research failures with explicit error recognition and domain-specific fallback strategies
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。
Handle web research failures by pivoting to internal knowledge for content 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 when a tool-calling agent does not call a tool, sends wrong arguments, loops without stopping, or needs a function schema. Guides a four-branch diagnosis and five-step schema repair. Do not use for framework-specific, MCP-server, or production-observability 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。
Extracts protocol message flow from source code, RFCs, academic papers, pseudocode, informal prose, ProVerif (.pv), or Tamarin (.spthy) models and generates Mermaid sequenceDiagrams with cryptographic annotations. Use when diagramming a crypto protocol, visualizing a handshake or key exchange flow, extracting message flow from a spec or RFC, diagramming a ProVerif or Tamarin model, or drawing sequence diagrams for TLS, Noise, Signal, X3DH, Double Ratchet, FROST, DH, or ECDH protocols.
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 custom fuzzers with LibAFL, the modular Rust fuzzing library. Covers composing observers, feedbacks, mutators, schedulers, and executors into a fuzzer for targets the standard tools do not fit. Use when writing a bespoke fuzzer or mutator, fuzzing a non-standard target or architecture, implementing a fuzzing research idea, or when libFuzzer and AFL++ lack the control you need.
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。
Improve academic paper writing quality for ML/CV/NLP-style papers with clear section structure, paragraph flow, and reviewer-facing presentation. Use when drafting or revising Abstract, Introduction, Related Work, Method, Experiments, or Conclusion; polishing figures/tables; checking claim-support alignment; or performing self-review before submission.
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 a game, engine or modding technique on the open web with archive-aware, rate-limit-safe searches — Wayback Machine/archive.today for dead forums (XeNTaX, Zenhax, old threads), GitHub code/repo search, Nexus/Steam Workshop/Thunderstore APIs, Reddit JSON, YouTube transcripts, plus archive snapshots as evidence. Use when starting work on a game ("how did people mod X before?"), when a documented tool/link is dead, when forum threads are login-gated (semi-auto handoff to the human), and before writing a field note so claims carry source URLs.
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 and contribute to the shared AI-modding knowledge base, where field notes record how specific games were modded, decompiled or reverse-engineered (exact versions, route, engine facts, verification, gotchas). Use before starting work on a game ("has anyone modded X?"), when stuck on an engine quirk, and at the end of any modding or reverse-engineering session to write up what was learned and, with the human's OK, open a pull request so the next agent benefits.
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。
Run fast, source-grounded UX research on the highest-signal problems users are experiencing with a user-specified digital product. Use when the user asks to research user pain, UX friction, onboarding issues, docs/help problems, developer experience friction, support pain, product workflow issues, or current user complaints for a named product.
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 broad or ambiguous life-sciences research requests to the right skills, normalize core entities, optionally parallelize independent evidence gathering with subagents when available, and synthesize a concise evidence-backed answer. Use when a user asks a general life-sciences question that could span multiple sources or analysis types.
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 to run deep research or AI-Q research through a reachable NVIDIA AI-Q Blueprint backend.
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。
Submit compact MetaboLights requests for study discovery and study-level metabolomics metadata. Use when a user wants concise MetaboLights summaries
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。
Submit compact EpiGraphDB API requests for ontology, literature, MR, gene-drug, and support-path evidence. Use when a user wants concise EpiGraphDB summaries
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。
Submit compact BioStudies and ArrayExpress API requests for free-text search and accession-based study retrieval. Use when a user wants concise BioStudies summaries
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 you do not know WHERE something belongs: you learned a lesson and are unsure which file takes it; you are about to create a new doc, folder, or convention; you are asking "should this be a skill, a note, or a chain file?"; you inherited a seat and want to know what SHOULD exist; or you are about to duplicate knowledge that already has a home. Also the trace-to-root: how a seat orients by reading one filename at each level from where it stands up to the fleet.
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。
深度研究编排方法论：澄清范围、拆解规划、并行调度子智能体调研、对抗式核验、综合成带引用的结构化报告。当任务需要多来源、可追溯、需事实核查的深度研究时使用此技能。
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。
Create a proto-persona from current research, market signals, and team knowledge. Use when you need a working customer profile before deeper validation.
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。
Run competitive research like an intelligence agency: eight collection disciplines (OSINT to MASINT), signal-to-inference chains, and fusion. Use when one-source research isn't enough.
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。
Map a market's segments, players, substitutes, and whitespace with cited evidence. Use when entering or re-evaluating a market before sizing, positioning, or picking competitors to study.
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 and draft a competitive battle card from public evidence — every claim labeled and sourced. Use when a rep needs a field-action card, not a research report.
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 a company, industry, or competitor set using web search and seven analytical lenses. Use when you need structured intel that feeds downstream PM skills.
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。