リサーチ・学習のスキル

Build structured ICP documentation by scraping case studies, testimonials, and solutions pages from your website. Produces firmographics, champion + economic buyer personas, pain points, decision criteria, anti-ICP, customer proof points, and voice-of-customer synthesis. Writes to marketing/icp/ICP.md as the canonical ICP every downstream skill reads. Triggers - "icp research", "ideal customer profile", "persona research", "customer segments", "who are our customers", "build ICP"

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。

Multi-provider deliberation panel for COMPLEX, multi-view questions — architecture, strategy, market research, and codebase sweeps. Runs a 4-stage deliberation across the provider fleet (diverge → contrarian red-team → adversarial verify → cited synthesis), the same multi-perspective rigour the plan-gate already applies to plan reviews, generalised to arbitrary questions. Use when one model's answer isn't enough and you want convergence THROUGH disagreement + verification, not a single opinion.

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。

Medical/scientific paper writing workflow skill. Manages the full pipeline from literature search to submission-ready manuscript. Creates and manages a project directory with IMRAD-format section files, literature matrix, reference management, and quality checklists. Supports both English and Japanese papers. Triggers: 'write paper', 'paper-write', 'start manuscript', '論文を書く', '論文執筆', '論文プロジェクト', 'manuscript', 'research paper', '原稿作成'.

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 whenever the user wants to find, shortlist, vet, or enrich US management consultancies — strategy, operations, executive coaching, leadership development, org-development/change management, PMO/program management, sales/revenue operations consulting. Triggers on "find me three top strategy consultancies in California", "shortlist boutique ops-consulting firms with healthcare experience", "we need an executive coach for our new CEO", or "pull contact info for these 10 consulting firm domains", even when described indirectly (post-merger integration help, change-management partner, fractional COO). Drives the ServiceGraph API (api.servicegraph.co) — a 100k+ US firm catalog filterable by industry, services, location, size, ratings. Skip in-house strategy hires, "help me build a strategy" do-the-work asks, framework comparisons (Lean vs Agile, BCG matrix, etc.), academic/MBA-program questions, life/career coaching for individuals, non-US firms, individual freelancers.

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Guided codebase exploration for understanding a repo's architecture, patterns, and domain language before contributing. Not issue-specific. builds general understanding. Use when exploring a new repo, wanting to understand how a project works, or preparing to become a regular contributor. Not for learning a framework or language you have never used. Use oss-learn-stack for that.

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 unclaimed open source issues that match the user's skills and experience level. Searches for issues created by maintainers/org admins, checks contribution eligibility, and ranks by learning value. Use when looking for an issue to contribute to, starting OSS contributions, or finding GSoC-friendly issues. Not for finding problems that nobody has filed an issue for yet. Use oss-find-real-issues for that.

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。

Learn unfamiliar technologies used in a repo by studying how the repo actually uses them. Finds patterns, explains concepts in context, and points to examples in the codebase. Use when a repo uses frameworks, languages, or patterns you haven't worked with before. Not for mapping a repo's architecture or domain language. Use oss-explore-repo for that.

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 other contributors' PRs to learn the codebase and build maintainer trust. Guides structured diff reading, helps formulate review comments, and teaches how to distinguish blocking issues from nits. Use when you want to learn a codebase by reviewing PRs, build trust with maintainers before contributing code, or practice code review on OSS repos. Not for reviewing your own PR — use oss-submit-pr for that.

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Research a topic in depth for the current or given task plan, by combining Internet/Web search with a grounding in the source artifacts of the project, and append the resulting research report to the "research" attachment of the task, optionally refining the plan by its recommendations. Use when the user wants to "research", "investigate", or "look into" a topic for a "task" or "plan".

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。

Insert, format, and cross-reference academic citations in Word (.docx) documents. Supports GB/T 7714-2015 (Chinese), IEEE, and APA 7th.

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。

Insert, format, and number math formulas in Word and LaTeX academic papers. Supports Chinese core journals and international journal formats. Invoke when user needs to insert LaTeX formulas into Word (OMML), validate formula formats per journal standards, or auto-number equations.

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。

Inserts, formats, and cross-references academic citations in docx. Invoke when user needs to insert references, fix citation order, add cross-reference hyperlinks, or reformat bibliography to Chinese (GB/T 7714) or international (IEEE/APA) standards.

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。

Insert, format, and cross-reference academic citations in Word (.docx) documents. Supports GB/T 7714-2015, IEEE, APA 7th.

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 preparing to engage a target account, researching a company before outreach, or building pre-call intelligence. Triggers: 'research this company', 'account brief for [company]', 'company research', 'what do I need to know about [company]', 'pre-outreach research'.

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。

Score deep research agents on benchmark tasks using factual verification, report-quality scoring, and process evaluation before model or workflow changes ship.

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 structured citation data from academic repositories using BeautifulSoup4 with lxml parser. Parses DOI metadata, author affiliations, and reference lists from PubMed, arXiv, and Semantic Scholar HTML.

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 a book or long document into a reusable AI mentor with source-grounded lessons, guided practice, citations, and persistent learning records.

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。

Lets agents operate Google NotebookLM/Gemini Notebook through a Python API, CLI, skill, MCP server, or REST server to create notebooks, add sources, ask cited questions, generate artifacts, and download exports.

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 NotebookLM through MCP or a local REST API to run cited Q&A, generate Studio artifacts, and manage high-volume research batches.

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 citation networks from Semantic Scholar API and CrossRef DOI metadata. Visualizes paper influence graphs using NetworkX, identifies seminal works, and tracks research lineage across fields.

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 want to benchmark and improve an existing repo skill through repeated evals, prompt mutations, and score tracking.

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。

Skill Optimization: Auto Research. Autonomously optimize any Claude Code skill by running it repeatedly, scoring outputs against binary evals, mutating the prompt, and keeping improvements. Based on Karpathy's autoresearch methodology. Use when: optimize this skill, improve this skill, run autoresearch on, make this skill better, self-improve skill, benchmark skill, eval my skill, run evals on. Outputs: an improved SKILL.md, a results log, and a changelog of every mutation tried.

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。

Build an AEO-first topical map optimized for AI search citation — entity clusters, query fan-out coverage, information gain scoring, and multi-platform distribution. Produces entity map, content node architecture, schema blueprint, and 90-day publishing calendar. Use when "topical map", "content architecture", "site structure", "topic clusters", "pillar content plan", "AEO map", "AI search architecture", "entity map", "what content should we build", or any request to plan a site's topical structure for AI search visibility.

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Run a learning retrospective on the Kai harness. Mines gate-failure logs and 30-day performance results into lessons, triages candidate lessons (promote/keep/retire), and graduates repeated lessons into enforced gate checks with golden corpus cases. Use when "retro", "what have we learned", "triage lessons", "promote lessons", "why does this keep failing", "harness retrospective", or monthly / after any heavy content sprint.

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。