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概要と使いどころ
Your education and edtech brain trust. 25 named personas across 7 cells covering learning science, curriculum design, AI tutoring, higher-ed strategy, edtech platforms, assessment, and workforce development.
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。
Your software-engineering brain trust. Named personas across 11 cells covering cloud architecture, reliability/SRE/observability, data and storage, security, FinOps, languages and runtimes, systems programming, web and frontend…
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。
Your healthcare and life sciences brain trust. 25 named personas across 7 cells covering drug discovery, medtech, biotech strategy, health policy, genomics, clinical trials, and healthcare economics.
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。
Your legal, IP, and regulatory brain trust. 31 named personas across 7 cells covering patent strategy, tech licensing, regulatory litigation, AI governance, open-source compliance, privacy law, and antitrust.
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。
Apply motion design principles for mobile apps covering timing curves, transitions, gestures, and performance-conscious animations. Use when implementing screen transitions, gesture-driven interactions, shared-element animations, or optimizing animation frame rates on iOS, Android, or Flutter.
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 academic paper review workflow covering self-review before submission and rebuttal writing after receiving reviewer feedback. Triggers on "review paper", "self-review", "write rebuttal", "respond to reviewers", "analyze review comments", "paper review".
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。
Post-acceptance conference preparation workflow covering presentation slides, academic posters, and promotion content. Triggers on "scholar publish", "conference preparation", "prepare presentation", "create poster", "write promotion", "post-acceptance".
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。
拼写变体标准化工具。统一英美拼写差异（colour→color、analyse→analyze 等），内置 153 词条 （含屈折形式 covered/covering 等），支持自定义词典扩展。当用户提到英美拼写统一、拼写变体、 British/American spelling 等需求时使用此skill。
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。
Turn one confirmed security finding into a disclosure-ready GitHub advisory with root cause, proof of concept, impact, and source evidence. Use for reporting an established vulnerability, not discovering or validating one.
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 repository-grounded AppSec threat model covering assets, trust boundaries, attackers, abuse paths, and mitigations. Use only for explicit threat-modeling requests, not general architecture or code review.
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 similar vulnerabilities across a codebase after discovering one instance. Uses pattern matching, AST search, Semgrep/CodeQL queries, and manual tracing to propagate findings. Adapted from Trail of Bits. Use after finding a bug to check if the same pattern exists elsewhere.
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 verification system covering build, types, lint, tests, security, and diff review before a PR.
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。
Example template for project-specific skill files covering architecture, patterns, testing, and deployment.
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。
Strategic guidance for designing modern data platforms, covering storage paradigms (data lake, warehouse, lakehouse), modeling approaches (dimensional, normalized, data vault, wide tables), data mesh principles, and medallion architecture patterns. Use when architecting data platforms, choosing between centralized vs decentralized patterns, selecting table formats (Iceberg, Delta Lake), or designing data governance frameworks.
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。
Manage Linux systems covering systemd services, process management, filesystems, networking, performance tuning, and troubleshooting. Use when deploying applications, optimizing server performance, diagnosing production issues, or managing users and security on Linux servers.
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。
Diagnose and fix concrete MSBuild property defects in projects and existing shared-file hierarchies. USE FOR: conditions, defaults, append versus overwrite, last-write-wins values, OS/TFM checks, portable paths, normalization, and reviews centered on those property defects. Property defects in Directory.Build.* remain in scope, including overwritten values across parent/child imports and conditions that run before TargetFramework is set, even when the fix changes import order or moves a property group to .targets. DO NOT USE FOR: placement-only or import-only requests with no concrete property defect, such as discovering shared files or choosing which file owns a target or customization (use directory-build-organization); item operations; target structure; broad reviews without a concrete property defect; non-MSBuild work.
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。
Invoke when the user asks to review, check, audit, or look over Qt6 C++ code — or suggest before committing. Runs deterministic linting (60+ rules) then six parallel deep- analysis agents covering model contracts, ownership, threading, API correctness, error handling, and performance. Reports only high-confidence issues (>80/100) with structured mitigations. Read-only — never modifies 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。
Invoke when the user asks to review, check, audit, or look over Qt6 QML code -- or suggest before committing. Runs deterministic linting (47+ rules) then six parallel deep- analysis agents covering bindings, layout, loaders, delegates, states, and performance. Optionally invokes system qmllint for type-level checks. Reports only high-confidence issues (>80/100) with structured mitigations. Read-only -- never modifies 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。
MUST read before generating images. Prompt-crafting guide for gpt-image-2.5 covering tool routing (native image_generation server tool vs the generate_image tool), model and quality selection, prompt structure, exact text rendering, reference-image editing, transparent assets, output formats, and multi-turn refinement.
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 chat with AI agents across the Universal Agentic Registry via the Hashgraph Online Registry Broker API. Use when discovering agents, starting conversations, finding incoming messages, or registering new agents.
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 reviewing, designing, or modifying Java enterprise systems and need a structured, repeatable ISO/IEC 25010:2023 quality-attribute review covering Functional Suitability, Performance Efficiency, Compatibility, Interaction Capability, Reliability, Security, Maintainability, Flexibility, and Safety, producing an engineering review report rather than an interactive ADR discovery. Part of Plinth Toolkit
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 need to generate an AGENTS.md file for a Java repository — covering project conventions, tech stack, file structure, commands, Git workflow, and contributor boundaries — through a modular, step-based interactive process that adapts to your specific project needs. This should trigger for requests such as Create AGENTS.md; Update AGENTS.md file; Add agent instructions; Generate contributor instructions for Java agents; Document repository conventions in AGENTS.md. Part of Plinth Toolkit
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 documentation specialist covering API documentation, technical writing, design documentation, migration guides, and changelog generation. Use when creating OpenAPI/Swagger specs, generating SDKs, writing user guides, creating README files, documenting architecture, writing design specs, creating ADRs, writing migration guides, or generating changelogs from git commits. Handles versioning, examples, developer experience, and user-facing documentation.
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 performance specialist covering analysis, optimization, load testing, and framework-specific performance. Use when identifying bottlenecks, optimizing code, conducting load tests, analyzing Core Web Vitals, fixing memory leaks, or improving application performance across all layers (application, database, frontend). Includes React-specific optimization patterns.
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。