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概要と使いどころ
Run Python code on cloud GPUs using Modal serverless platform. Use when you need A100/T4/A10G GPU access for training ML models. Covers Modal app setup, GPU selection, data downloading inside functions, and result handling.
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。
Query PubChem via PUG-REST API/PubChemPy (110M+ compounds). Search by name/CID/SMILES, retrieve properties, similarity/substructure searches, bioactivity, for cheminformatics.
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。
Orchestrate workflows across multiple applications and APIs — inter-app coordination, data handoff, and multi-system task completion.
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。
System and API design guidance covering component boundaries, data flow, integration patterns, and scalability considerations.
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 whenever an Agent needs to query, find, install, deploy, update, tag, adopt, diagnose, or safely remove Skills Hub content, including natural-language requests to manage Skills for Codex, Claude Code, Cursor, or another Agent. Always use the Skills Hub CLI workflow instead of editing Skill directories or the database.
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。
Elite AI context engineering specialist mastering dynamic context management, vector databases, knowledge graphs, and intelligent memory systems. Orchestrates context across multi-agent workflows, enterprise AI systems, and long-running projects with 2024/2025 best practices. Use PROACTIVELY for complex AI orchestration.
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 Chain-of-Verification (CoVe) on a draft or a block of text with factual claims. Spawns the `claim-verifier` agent in a fresh context (never a conversation fork) so it never sees the draft — then reports which claims are supported, contradicted, or unverifiable. Use when user says "verify these citations", "check the claims in X", "did I hallucinate anything", "fact-check this draft", "run CoVe on this", or after any text generation that asserts facts about papers, datasets, or numerical results. NOT for style/grammar review (use `/proofread`) or substance review (use `/review-paper`).
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。
Snapshot the computational environment for a replication package — detects the analysis stack (R / Stata / Python) and emits the right lockfiles (renv.lock + sessionInfo.txt, requirements.txt / environment.yml / uv.lock, Stata version + ado package list), records seeds and RNG kind, optionally writes a pinning Dockerfile, and produces a paste-ready "Computational requirements" block. Use when user says "capture the environment", "snapshot my dependencies", "pin the versions", "make a renv.lock / requirements.txt", "make this byte-reproducible", or before releasing a replication package to openICPSR / the AEA Data Editor.
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。
Interactive interview that formalizes a fuzzy research idea into a structured spec (RQ, hypotheses, identification, data needs, empirical strategy). Use when user says "interview me", "help me think through this idea", "I have a half-baked idea", "formalize this into a project", "walk me through framing a study". Multi-turn Q&A; saves spec to disk. NOT for lit review (`/lit-review`) or ideation from scratch (`/research-ideation`).
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 Stata replication pipeline — scaffolds numbered `.do` files in `scripts/stata/`, executes them via the `stata-mcp` MCP server, captures logs and outputs to `output/`, and produces publication-ready tables (esttab) and figures (graph export). Mirrors `/data-analysis` for R-first projects. Use when user says "stata replication", "set up Stata pipeline", "scaffold the .do files", "run Stata analysis", "AEA replication package in Stata", or when a project's analysis language is Stata not R.
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Generate a co-author / collaborator handoff brief for a multi-author, multi-machine project — summarizing what changed since the last brief (git delta), the current state of each artifact (manuscript, analysis, slides), open questions, how to reproduce locally, and any restricted-data access steps. Use when user says "coauthor brief", "handoff brief", "bring my coauthor up to speed", "what changed since last week", "onboard a collaborator", "write a handoff for [name]", or before sending a co-author the repo. NOT a commit or a checkpoint — it is the cross-machine, cross-person summary `meta-governance.md` only partially covers.
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。
Creates explicit validation checkpoints (verification gates) between project phases to catch errors early and ensure quality before proceeding. Use when the user asks about quality gates, milestone checks, phase transitions, approval steps, go/no-go decision points, or preventing cascading errors across a multi-step workflow. Produces acceptance criteria checklists, automated CI gate configurations, manual sign-off requirements, and conditional review rules for scenarios such as security changes, API changes, or database migrations.
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Applies systematic tracing and isolation techniques to pinpoint exactly where a bug originates in code. Use when a bug is hard to locate, code is not working as expected, an error or crash appears with unclear cause, a regression was introduced between recent commits, or you need to narrow down which component, function, or line is faulty. Covers binary search debugging, git bisect for regressions, strategic logging with [TRACE] patterns, data and control flow tracing, component isolation, minimal reproduction cases, conditional breakpoints, and watch expressions across TypeScript, SQL, and bash.
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。
Privacy planning reference for data-flow reasoning, standards mapping, and DPIA thresholds
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。
Diagnoses and repairs repository setup and guarded Git workflows for Claude Code or Codex — environment repair, startup sync, hook auditing, collaborator handoff. Use when a repo won't run, a teammate onboards, hook output duplicates, or commit/push/conflict needs guarding. Not for lost-commit recovery (use git-safety-net), GitHub ops (use github-ops), or history scrubbing (use github-sensitive-data-cleanup).
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。
Audits already-rendered UI and Markdown/Obsidian image layout — web app, deck/slide, dashboard, design-system, or Electron/native app — via real-browser/native-app journeys and a Playwright sweep. Use after UI implementation to find typography, overflow, responsive, routing, data-viz, browser-output, or native-shell defects, or to compare a render against a reference. Not for greenfield UI design (use ui-designer) or QA-program setup (use qa-expert).
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。
Analyzes and optimizes application performance across frontend, backend, and database layers. Use when diagnosing slowness, improving load times, optimizing queries, reducing bundle size, or when asked about performance issues.
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。
Convex backend development guidelines. Use when writing Convex functions, schemas, queries, mutations, actions, or any backend code in a Convex project. Triggers on tasks involving Convex database operations, real-time subscriptions, file storage, or serverless functions.
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。
React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.
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。
Implement or modify web UI in React, Next.js, or Angular. Use for components, pages, styles, forms, and frontend state or data flows.
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。
Implement Flutter, React Native, or native Swift apps. Use for mobile screens, widgets, platform integrations, and application data flows.
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。
Perform codebase analysis and architecture mapping as the first phase of a security assessment. Explores the tech stack, frameworks, entry points, data flows, and trust boundaries. Outputs sast/architecture.md. Run this before any vulnerability detection skill. Use when asked to analyze a codebase for security or when sast/architecture.md does not yet exist.
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 pull data out of one or more PDFs (invoices, bank/credit-card statements, receipts, reports, tables) and put it into a spreadsheet. pdf_read is one of the most-used tools; this codifies the read-PDF → structure → write-Excel workflow. Powered by LMCP on macOS and Windows.
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。
Regression testing strategies for AI-assisted development. Sandbox-mode API testing without database dependencies, automated bug-check workflows, and patterns to catch AI blind spots where the same model writes and reviews code.
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。