Research

Create and edit Mermaid diagrams for software engineering work, architectural ideas, and technical documentation. Use when the user asks to create, edit, or work with Mermaid diagrams. Provides comprehensive syntax references, common pitfalls, styling guidance, and software architecture patterns.

Agent-optimized Test-Driven Development workflow based on research from Codex, CodeT, Self-Debugging, TICoder, and SWE-bench Verified. Use when fixing bugs (generate fail-to-pass test first), implementing new features (acceptance tests first), or when user requests "TDD", "test-first", or "test-driven" approach. Provides high-confidence code changes with comprehensive test coverage.

Create a new TypeScript exercise with starter code, test cases, and reference solution

Эксперт анализа распределений. Используй для statistical distributions, data analysis и hypothesis testing.

A workflow for capturing evidence and citations to create reproducible analyses and audit trails.

Chain multiple operations together in pipelines. Use for multi-step workflows, combining research with analysis, and complex automated tasks.

Live testing and validation of production research API for strategy optimization loops

Chaos experiment design methodology. Hypothesis formation, success criteria definition, blast radius control, validation patterns, and SLI monitoring for effective chaos engineering.

Codex MCP tool reference. Supplemental parameter docs for codex tool (tuannvm/codex-mcp-server).

[REPLACE] Teach concepts and demonstrate patterns with examples. Use when [REPLACE with specific triggers].

Research GitHub, GitLab, and Bitbucket repositories using DeepWiki MCP server. Use when exploringunfamiliar codebases, understanding project architecture, or asking questions about how a specificopen-source project works. Provides AI-powered repo analysis and RAG-based Q&A about source code.NOT for fetching library API docs (use fetching-library-docs instead) or local files.

Use PROACTIVELY when creating research reports, experiment writeups, technical whitepapers, or empirical study documentation. Orchestrates the complete benchmark report pipeline with structure, diagrams, hi-res PNG capture, and PDF export. Provides working scripts, CSS templates, and complete command sequences for publication-quality AI/ML benchmark reports. Not for slides, blog posts, or simple README files.

Search and retrieve academic literature from multiple databases.LOAD THIS SKILL WHEN: User says "搜尋文獻", "search literature", "find papers", "PubMed", "學術搜尋" | needs to find research articles | starting literature review.CAPABILITIES: PubMed search, MeSH term expansion, citation metrics, batch retrieval.

Probability, distributions, hypothesis testing, and statistical inference. Use for A/B testing, experimental design, or statistical validation.

Classifies information into PACER categories (Procedural, Analogous, Conceptual, Evidence, Reference) and recommends appropriate digestion protocols. Use when learning new material, studying, reading educational content, processing information for retention, or when user asks about how to study or remember something.

Comprehensive research, analysis, and content extraction system. Multi-source parallel research using available researcher agents. Deep content analysis with extended thinking. Intelligent retrieval for difficult sites. Fabric pattern selection for 242+ specialized prompts. USE WHEN user says 'do research', 'extract wisdom', 'analyze content', 'find information about', or requests web/content research.

Analyze arXiv research papers and explain them in accessible terms. Use when the user mentions arXiv, research paper, academic paper, scientific paper, preprint, or provides an arxiv.org URL.

Generate comprehensive philosophy and standards documents for any domain (UX design, landing pages, email outbound, API design, etc.). Load when user says "create philosophy doc", "generate standards for [domain]", "build best practices guide", or "create benchmarking document". Conducts deep research, synthesizes findings, and produces structured philosophy documents with principles, frameworks, anti-patterns, checklists, case studies, and metrics.

Research external APIs/services/libraries for feature implementation. Interviews user, researches options, confirms choice, gathers implementation notes. Creates .claude/plans file.

Comprehensive toolkit for creating, analyzing, and visualizing complex networks and graphs in Python. Use when working with network/graph data structures, analyzing relationships between entities, computing graph algorithms (shortest paths, centrality, clustering), detecting communities, generating synthetic networks, or visualizing network topologies. Applicable to social networks, biological networks, transportation systems, citation networks, and any domain involving pairwise relationships.