Research

PolicyEngine visual identity - colors, fonts, logos, and branding for web apps, calculators, charts, and research

Token-efficient library API documentation fetcher using Context7 MCP with 77% token savings.Fetches code examples, API references, and usage patterns for published libraries (React,Next.js, Prisma, etc). Use when users ask "how do I use X library", need code examples,want API syntax, or are learning a framework's official API. Triggers: "Show me React hooks","Prisma query syntax", "Next.js routing API". NOT for exploring repo internals/source code(use researching-with-deepwiki) or local files.

Implements Schema.org structured data for AndesRC articles. Adds ExercisePlan, HowTo, and FAQPage markup. Optimizes meta titles and descriptions. Use before publication.

Expert guidance for writing high-quality academic and research papers. Use when the user wants to write, structure, revise, or improve academic papers, research articles, conference papers, or technical reports. Provides comprehensive support for all stages from planning to final polish.

Generate publication-style newsletters and executive briefs for 360 Social Impact Studios by synthesizing updates from Asana, Gmail, and Google Drive into professionally designed, interactive HTML dashboards with data visualizations. Supports both confidential executive briefs and public-facing newsletters.

Full text access via Europe PMC, CORE, and other open access sources. Triggers: 全文, fulltext, PDF, open access, 免費下載, PMC, 開放取用

Extract learnings from completed swarm work for persistent memory storage. Analyzes swarm_record_outcome data to identify corrections, decisions, and insights. Stores findings in Memory Lane for future reference. Use when subtasks complete with notable learnings or when you want to capture what worked/didn't work.

User-specific git workflow preferences and edge case handling. Documents commit message format requirements and pre-commit hook retry logic specific to this user. Use when creating commits or handling pre-commit hook failures.

Use when encountering bugs, test failures, unexpected behavior, errors, or performance problems - dispatches systematic-debugging-agent that enforces 4-phase process (root cause investigation, pattern analysis, hypothesis testing, implementation) to prevent quick-fix attempts and ensure proper debugging

Guide interactive research and POC creation to understand features deeply. This skill should be used when planning to implement a new feature and needing to research design patterns, understand integration points in the codebase, consult documentation via MCP Deep Wiki, or create minimal POCs to validate concepts. Can receive CDC.md from feature-specification as input for clear requirements.

Expert prompt engineering for LLMs and AI agents. Use when users request help writing, reviewing, or improving prompts for chatbots, AI agents, system prompts, instruction sets, or any LLM-based application. Applies research-backed techniques to minimize hallucinations and maximize reliability.

Standards, conventions, and struct tag reference for models

Manim（Mathematical Animation Engine）を使用してアニメーション動画を作成します。このスキルは、(1) 解説動画やビジュアライゼーションの作成、(2) プレゼンテーション動画、(3) ロゴアニメーション、(4) インフォグラフィック、(5) 教育コンテンツ、(6) 3Dアニメーション、(7) アルゴリズムやデータ構造の可視化に使用します。2D/3Dシーン、LaTeX数式、グラフ、TTSナレーション、BGMなどをサポートします。

This skill should be used when the user asks to "debug notebook", "inspect notebook outputs", "find notebook error", "read traceback from ipynb", "why did notebook fail", or needs to understand runtime errors in executed Jupyter notebooks from any source (marimo, jupytext, papermill).

Search the web for up-to-date information using GPT-5.2 with web search and high reasoning. Prefer this over webfetch when you need to research complex queries, find current info across multiple sources, get recent news, up-to-date documentation, or verify facts that may have changed since your training cutoff. Returns cited sources.

Hybrid skill for OpenCode plugin development - behavioral patterns for agents and technical reference for humans

Sophisticated multi-agent AI research system that conducts comprehensive, academic-quality research on complex topics through orchestrated specialist agents. Use for deep research requiring academic, technical, and data-driven perspectives with quality assurance and comprehensive reporting.

Synthesize knowledge from multiple sources into Zettelkasten notes for Logseq. Use when creating wiki pages, integrating academic research, or building interconnected knowledge with [[links]] and

Perform comprehensive OSCAL validation using community-inspired patterns including JSON schema validation, business rule validation, cross-reference checking, and best practices from IBM Trestle, oscal-pydantic, and Lula. Use for thorough document quality assurance.

Guide agents through structured research including planning, multi-query execution, source analysis, and synthesis. Use for comprehensive topic research, deep investigation, or creating research reports. Keywords: research, investigate, deep dive, comprehensive, analysis, synthesis, report.