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概要と使いどころ
Use the DataSciencePython tutorial/example collection through modern self-contained helpers for Python data-science resources, statsmodels logistic regression, scikit-learn Kaggle-style tabular classifiers, and Twitter JSONL extraction.
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 Atomic Agents to build schema-driven agents, integrate tools and MCP connectors, adapt example applications, and maintain the monorepo safely.
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 repo skill for Agent Lightning package tasks: authoring trainable agents, tracing rewards and spans, running LightningStore/Trainer loops, using agl CLI services, choosing examples, and troubleshooting optional backends.
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。
Generate or update an Agent Skill that teaches consumers one npm or local package the user maintains, including framework modules and wrappers. Tests each example against the installed version. Use when a maintainer asks for a package Skill, a SKILL.md for their library, or a Skill update after a release.
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。
Evaluate Agent Skill design quality with an opinionated, practice-derived rubric informed by public specifications and examples. Use when reviewing, auditing, comparing, or improving SKILL.md files and skill packages. Produces evidence-backed findings, optional multi-dimensional scoring, and prioritized changes; treat the result as diagnostic guidance, not official certification or a universal standard.
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。
只读检索小红书公开内容，并把账号数据、标题、封面、互动量、作者近期内容和低粉爆款整理成可追溯证据。用户要求查公开账号或笔记数据时使用；不得点赞、收藏、评论、发布、删除或导出登录凭证。 English: Read-only research for public Xiaohongshu content, collecting traceable evidence such as account data, titles, covers, engagement, recent posts, and low-follower breakout examples. Use for public account or post research; never like, save, comment, publish, delete, or export credentials.
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。
为已经确定的小红书内容设计封面文字和画面布局，包括关键词、人物与场景位置以及 A/B 方案。用户要做小红书封面、参考爆款封面，或检查封面是否符合账号视觉调性时使用。 English: Design cover copy and visual composition for an approved Xiaohongshu post, including keywords, subject placement, scenes, and A/B options. Use to create or review a cover against successful examples and the account's visual style.
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。
把已验证的传播机制转成适合目标账号的内容选题，并完成生成、迁移、评分和筛选，让选题自然连接人设、产品或门店。用户要从低粉爆款、垂直样本、邻近受众或跨赛道内容中寻找新选题时使用。 English: Turn validated content mechanisms into topics that fit the target account, then generate, adapt, score, and filter them while connecting naturally to the persona, product, or store. Use to find ideas from low-follower breakouts, niche examples, adjacent audiences, or other categories.
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。
Generate comprehensive, developer-friendly API documentation from code, including endpoints, parameters, examples, and best practices
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。
Guide to implementing homomorphic encryption for privacy-preserving computation under GDPR. Covers scheme selection (BFV, BGV, CKKS, TFHE), Microsoft SEAL, IBM HELib, and Google FHE transpiler. Includes performance benchmarks, parameter tuning, and basic HE example code for encrypted arithmetic operations.
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 when the user requests current information, documentation, coding examples, or web research beyond the knowledge cutoff. Queries Google's AI Search mode to retrieve comprehensive AI-generated overviews with source citations from 100+ websites. Returns markdown with inline footnoted references [1][2][3]. You will receive a detailed Markdown file with references and information summarized directly from Google's AI search. Ideal for you to get new information and clues for further 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。
Use when a skill is brittle, drifting, repeatedly failing, or needs a Reliable Skill Contract. Trigger for phrases like skill lifeguard, reliable skill, self-maintaining skill, negative examples, verification checkpoints, drift signals, replay hooks, or failure log to skill patch. Audits or patches skills so high-value workflows include explicit forbidden behaviors, checkpoints, machine-checkable done conditions, replay or smoke hooks, and drift detection.
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。
Scaffold or standardize a production-ready repository structure with specs, source layout, tests, CI, agent context, config examples, release notes, and operational docs. Use when starting a new repo, turning a prototype into a maintainable project, adding missing repository foundations, or creating a repo skeleton before implementation. For AGENTS.md-only context scaffolding, use agentsmd-scaffold.
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。
n8n workflow automation knowledge base. Provides n8n node information, node functionality details, workflow patterns, and configuration examples. Covers triggers, data transformation, data input/output, AI integration, covering 10 nodes. Keywords: n8n, workflow, automation, node, trigger, webhook, http request, database, ai agent.
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。
Recommend font combinations for different use cases. Provide Google Fonts alternatives to premium fonts with hierarchy examples.
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。
Develop art direction for image generation with curated style cards distilled from Open Image Prompts. Use when choosing or comparing visual directions, improving an existing generation prompt, or translating a subject, use case, or supplied image into a compact creative spec. Use img-gen-prompts for real archive examples, exact source prompts, or gallery browsing.
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 distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, artifacts, posters, or applications (examples include websites, landing pages, dashboards, React components, HTML/CSS layouts, or when styling/beautifying any web UI). Generates creative, polished code and UI design that avoids generic AI aesthetics.
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 the required PR-ready summary block, branch suggestion, title, and draft description for openai-guardrails-python after runtime, tests, examples, build/test configuration, or behavior-impacting docs 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。
Run the mandatory verification stack when changes affect runtime code, tests, examples, or build and test behavior in the OpenAI Guardrails Python repository.
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。
Assign, validate, normalize, and explain Luhmann/Zettelkasten-style project-note codes for Chinese book manuscripts, Obsidian Markdown folders, Mandala-Grid section files, HyperCard Markdown stacks, and project-note JSON to EPUB workflows. Use when Codex needs to scan folders for 部/章/節/項/目 numbering, generate stable card ids, insert branch codes without renumbering existing notes, map letter-coded branches to Obsidian Mandala sections, preserve K### keyword index cards, sanitize private catalogs into public examples, or prepare card IDs for EPUB and HyperCard output.
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。
Automatically reduces bug-triggering test cases to minimal form while preserving the failure. Use when debugging with large, complex test cases that need simplification, reproducing bugs with minimal examples, or creating regression tests from verbose failure scenarios. Takes a failing test and systematically removes unnecessary inputs, steps, assertions, and code using delta debugging and other reduction algorithms. Supports unit tests, integration tests, input files, and multiple programming languages (Python, JavaScript, Java, C/C++).
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。
Proposes secure remediation strategies for detected security vulnerabilities including buffer overflows, injection risks, insecure deserialization, improper authentication, and unsafe cryptographic usage. Provides recommended security checks, safer API alternatives, design-level changes, code examples, trade-off analysis, and prioritized remediation plans. Does NOT automatically modify code unless explicitly requested.
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。
Systematic external reference searching across documentation, open-source repositories, and web resources. Use when working with unfamiliar libraries, APIs, or when needing production-quality implementation examples.
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。
Explains runtime errors and compilation failures with actionable debugging guidance. Use when Python or Java code throws runtime exceptions (NullPointerException, TypeError, AttributeError, etc.), compilation errors (syntax errors, type mismatches, import failures), or dependency issues. Analyzes error messages, stack traces, and code context to identify root causes and provide concrete fixes with examples. Distinct from test-related errors - focuses on errors during normal code execution and build processes.
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。