Research

Create professional research posters in LaTeX using beamerposter, tikzposter, or baposter. Support for conference presentations, academic posters, and scientific communication. Includes layout design, color schemes, multi-column formats, figure integration, and poster-specific best practices for visual communication.

Produce grounded audio briefs by chaining source-scoped input, citation verification, dialogue dramatization, and multi-speaker TTS orchestration. Use for “Audio Overview” style outputs.

Actively test and verify specific claims about correctness, safety, or behavior through experiments and observable evidence. Use when: (1) asked to verify a claim about code behavior, correctness, or performance, (2) statements about behavior appear without verification evidence or test results, (3) language includes modal uncertainty markers like "should work" where verification is possible, (4) discussion analyzes implementation through reading rather than execution and observation.

Business analysis skill for requirements gathering, market research, strategic analysis, and project brief creation. Use when users need to (1) Create comprehensive project briefs, (2) Conduct market or competitive analysis, (3) Facilitate brainstorming sessions, (4) Define problems and validate assumptions, (5) Elicit requirements through structured questioning, (6) Create user personas, or (7) Analyze project feasibility and scope

ALWAYS ACTIVE: Use Language Server Protocol (LSP) for semantic code understanding and intelligent editing. This skill applies to ALL coding tasks. Use Serena's LSP tools for: (1) semantic navigation and symbol discovery, (2) finding references and dependencies, (3) symbol-level editing and refactoring, (4) understanding project structure. Dramatically improves code quality and reduces token usage compared to text-based grep/read operations. Activate for any code-related work.

MANDATORY skill creation framework for ALL skill creation requests. USE WHEN user wants to create, validate, update, or canonicalize a skill, OR user mentions skill creation, skill development, new skill, build skill, OR user references skill compliance, skill structure, or skill architecture.

Interview preparation system with STAR story management, company deep-dives, and salary negotiation. Build and practice behavioral stories, research companies thoroughly, and prepare for offer negotiations. Triggers - "prepare for interview", "practice STAR", "show my stories", "deep dive company", "prep negotiation", "compare offers", "interview prep", "behavioral questions".

Technical documentation specialist - create docs, API references, user guides for technical and non-technical audiences

Guide LaTeX document authoring following best practices and proper semantic markup. Use proactively when: (1) writing or editing .tex files, (2) writing or editing .nw literate programming files, (3) literate-programming skill is active and working with .nw files, (4) user mentions LaTeX, BibTeX, or document formatting, (5) reviewing LaTeX code quality. Ensures proper use of semantic environments (description vs itemize), csquotes (\enquote{} not ``...''), and cleveref (\cref{} not \S\ref{}).

Query Perplexity.ai directly from the terminal to find answers to research questions, current events, and detailed explanations. Returns structured JSON output for programmatic parsing. Use when you need current information, comprehensive answers with source references, or want to avoid making separate web search requests.

Conduct comprehensive, multi-source research on any topic using web search, documentation lookup, and critical analysis. This skill should be used when users request thorough investigation, deep research, or comprehensive analysis of topics including but not limited to AI systems, technology trends, academic subjects, business strategies, or current events. | 任意のトピックに対して、Web検索、ドキュメント参照、批判的分析を用いた包括的な調査を実施。徹底的な調査、詳細なリサーチ、包括的な分析が必要な場合や、AIシステム、技術トレンド、学術的テーマ、ビジネス戦略、時事問題などについて深く知りたい場合に使用。

Use when design is complete and you need detailed implementation tasks - creates tracked MCP issues with exact file paths, complete code examples, and verification steps. Optional reference plan file for architecture overview.

Use when working on totalaud.io experimental project - ensures experimental code stays isolated from Total Audio Platform production code, prevents cross-contamination of dependencies, validates no production impact from experimental features

Use when beginning a new conversation to work on an open-ended goal, loading context from previous iterations through iteration journals

Use automatically when prompts exceed 3000 characters, files exceed 500 lines, or large files are referenced - enforces complete line-by-line reading protocol with quantitative comprehension verification before processing, preventing partial comprehension and ensuring thorough understanding

Streamlined guide for Google Ads API queries via MCP. Use when querying campaign performance, keyword metrics, conversion data, auction insights, or ad group analysis. Reduces context overhead by providing curated field references and common query patterns. Triggers on Google Ads, SEM performance, campaign analysis, keyword research, or auction insights requests.

Executes Perplexity AI queries via unified Python CLI. Use when conducting web research, asking questions with citations, deep research tasks, reasoning problems, or searching for up-to-date information.

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes - four-phase framework (root cause investigation, pattern analysis, hypothesis testing, implementation) that ensures understanding before attempting solutions

Identifies high-quality leads for your product or service by analyzing your business, searching for target companies, and providing actionable contact strategies. Perfect for sales, business development, and marketing professionals.

This skill should be used whenever users ask food-related questions, meal suggestions, nutrition advice, recipe recommendations, or dietary planning. On first use, the skill collects comprehensive user preferences (allergies, dietary restrictions, goals, likes/dislikes) and stores them in a persistent database. All subsequent food-related responses are personalized based on these stored preferences.