Research

Specialized skill for editing and refining EAD2002 finding aids for the Terrence Kaufman Papers at the Archive of Indigenous Languages of Latin America (AILLA), Lillas Benson Latin American Studies and Collections, University of Texas at Austin. Use when working with KaufmanEAD.xml, implementing staff feedback, validating against EAD2002 standards, or referencing institutional finding aid examples.

Conduct parallel multi-angle research on programming topics. Break down complex research questions into 3-10 specific investigation avenues, delegate each to parallel sub-agents, and synthesize findings with working code examples and sources. Use when investigating error messages, comparing solutions, or exploring implementation approaches.

Use this skill when the user mentions "plan", "track", "spec", "conductor", asks about project progress, or references conductor files like plan.md, spec.md, tracks.md, product.md, tech-stack.md, or workflow.md. Also use when the user wants to understand the Conductor methodology or Context-Driven Development workflow.

Enforces visibility pattern for testability by detecting private methods that prevent unit testing (causes 20-40% coverage loss). References authoritative style guides rather than duplicating. Auto-refactors code to private[module] object pattern with user approval. Detects inline lambdas and suggests extraction to named functions ("laws"). Blocks during scala-ninja review (Phase 2) as peer review rejection point.

Create comprehensive technical documentation for code systems including data flow diagrams, architecture overviews, algorithm documentation, cheat sheets, and multi-file documentation sets. Use when documenting pipelines, algorithms, system architecture, data flow, multi-stage processes, similarity algorithms, or creating developer onboarding materials. Covers Mermaid diagrams, progressive disclosure, critical patterns, JSON schemas, Pydantic models, and print-friendly reference materials.

Use when working with Luban game configuration tool - covers schema definition, Excel data filling, code generation, polymorphic types, validators, localization, and roblox-ts integration. Provides indexed reference to complete Luban documentation by topic

Manage Google Drive files and folders. Load when user mentions 'google drive', 'drive', 'upload file', 'download file', 'share file', 'create folder', or references cloud file storage operations.

Systematic debugging guide for Nomos compilation failures. Use this when compilation fails, providers won't start, references are unresolved, or builds produce unexpected output.

One-step preference alignment using Odds Ratio Preference Optimization (ORPO) (triggers: ORPO, preference optimization, alignment, ORPOTrainer, log_odds_ratio, binary preference).

Guide selection and interpretation of statistical hypothesis tests. Use when: (1) Choosing appropriate test for research data, (2) Checking assumptions before analysis, (3) Interpreting test results correctly, (4) Reporting statistical findings, (5) Troubleshooting assumption violations.

Use this whenever a user wants to add a new feature or explitly states to research a feature/API or building a plan for a new feature. It itnerviews the user for feature details (if not provided), research the best API/service for their needs, confirm choice, then gather all implementation notes for their request and save them as a .claude/plans file.

Generate comprehensive Product Requirements Documents for web and mobile apps using lean startup methodology. Perfect for solo entrepreneurs and new product concepts. Creates hypothesis-driven PRDs with MVP focus, user stories, and technical specifications. Exports to multiple formats including Markdown, HTML, and DOCX. Use when planning new products, defining MVPs, or documenting product vision for AI coding assistants.

Summarize robotics-related text, research papers, or lecture notes into concise, clear, and structured summaries. Use when user asks to condense or simplify robotics content.

Personal copy editor and content enhancer for Obsidian vault notes. Use when the user requests editing, enhancement, copyediting, critique, or improvement of markdown files. Typical triggers include "edit this file", "clean up these notes", "enhance this draft", "give me feedback on", "polish this content", "expand my shorthand", or "add links to this". Handles diverse content types including technical documentation, research notes, essays, Substack posts, administrative notes, and personal writing. Always preserves original content and appends enhanced version below a separator line.

Expert CV/resume writer with deep ATS optimization, job description analysis using chain-of-thought reasoning, industry-specific formatting (tech, business, creative, academic, executive), and strategic career positioning. Use when users need help with creating or updating CVs/resumes, analyzing job descriptions to identify keywords and requirements, optimizing existing CVs for ATS systems, tailoring CVs for specific jobs or industries, improving CV sections or bullet points, translating experience into achievement-driven narratives, addressing career gaps or transitions, or selecting appropriate CV formats for different fields and career levels.

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.

"Is this ACTUALLY verified, or did I just say it is?" - Ralph-wiggum methodology applied to factual accuracy. Use when (1) claims require evidence not assumption, (2) verification must be demonstrable, (3) single-pass investigation insufficient, (4) factual accuracy is critical. Provides the loop logic: iterate until verification thresholds met. Does NOT trigger for: opinions, preferences, how-to instructions, or when user explicitly wants quick answer.

Expert deep research including multi-source verification, fact-checking, and comprehensive analysis

Comprehensive context engineering and prompt patterns for AI agents. Covers code review, financial systems, KPI systems, data integration MVP, and modern best practices. Based on 2025 research from Anthropic, LangChain, and industry leaders.

Transforms an academic paper into deep, multi-layered understanding. Use when asked to explain a paper, break down a research paper, understand an arXiv paper, or build intuition for a technical concept from a paper. Generates explanations at multiple levels plus visual intuition diagrams.