Research

CC2.0 seven-function research workflow (observe, reason, create, orchestrate, learn, verify, deploy) for categorical AI research. Use when conducting systematic research on categorical AI topics, coordinating multi-stream research workflows, applying categorical foundations to research methodology, or implementing the L5 meta-prompting research framework.

Systematic analysis patterns for categorical AI papers (Gavranović, de Wynter, Bradley, Zhang). Use when analyzing academic papers on categorical deep learning, extracting categorical structures from AI research, mapping meta-prompting concepts to category theory, or building comprehensive literature reviews on categorical approaches to AI.

Canonical specification format reference. Use when understanding the canonical spec schema, field requirements, provider-agnostic specification structure, or validating specifications against the schema.

TAM/SAM/SOM calculation, competitor analysis, and market trends identification. Use when analyzing markets, validating business ideas, or entering new markets.

Quick lookup of specific facts about Bottlerocket with citations

Universal context management and planning system. PROACTIVELY activate for: (1) ANY complex task requiring planning, (2) Multi-file projects/websites/apps, (3) Architecture decisions, (4) Research tasks, (5) Refactoring, (6) Long coding sessions, (7) Tasks with 3+ sequential steps. Provides: optimal file creation order, context-efficient workflows, extended thinking delegation (23x context efficiency), passive deep analysis architecture, progressive task decomposition, and prevents redundant work. Saves 62% context on average. Essential for maintaining session performance and analytical depth.

AI-led stakeholder interviews using LLMREI research-backed patterns. Conducts structured interviews to elicit requirements through context-adaptive questioning, active listening, and systematic requirement extraction.

Use when implementing chaos engineering, designing fault injection experiments, or building resilience testing practices. Covers chaos principles and experiment design.

Research across Notion and synthesize into structured documentation; use when gathering info from multiple Notion sources to produce briefs, comparisons, or reports with citations.

Conduct systematic scientific literature reviews by integrating multi-source searches, iterative analysis, and synthesis into well-structured reports with proper citations.Use this skill when you need to: synthesize knowledge across multiple research domains, identify research gaps, track the evolution of methodologies, evaluate evidence quality, or write comprehensive literature reviews for academic papers, grant proposals, or research projects.Key capabilities: multi-database search strategies, iterative query refinement, content analysis and summarization, thematic synthesis, citation management, quality assessment, bias detection, and structured report generation with multiple output formats.

Comprehensive LaTeX documentation from Overleaf Learn tutorials

Diagnose and fix bugs using evidence-based investigation. Requires runtime evidence before fixes—never guess based on code alone. Covers hypothesis-driven debugging, instrumentation logging, Lua errors, taint issues, combat lockdown, and API failures. Triggers: error, bug, debug, fix, crash, taint, nil value, diagnose, hypothesis, runtime, evidence, instrumentation.

Meta knowledge for creating Claude skills. Provides templates, best practices, and patterns for building effective skills with routing tables and reference files. Load this when creating new skills or understanding the skill system. Triggers: create skill, new skill, skill template, skill architecture, SKILL.md.

Quick reference for common SQL patterns, CTEs, window functions, and indexing strategies. Triggers on: sql patterns, cte example, window functions, sql join, index strategy, pagination sql.

Expert assistant for the Okyline schema language. Okyline enables JSON data validation by example, where constraints are expressed inline on field names. Use when creating, editing, or converting JSON Schema, Avro, or other schema formats to Okyline, or when answering questions about Okyline syntax and features. This skill should be triggered whenever the user mentions Okyline, references .oky files, or asks about example-driven JSON schema validation.

Convert GitHub repositories into LLM-friendly text. Use when you need to analyze external codebases, research unfamiliar libraries, understand third-party project structure, or ingest code from GitHub URLs (public/private, supports subdirectories).

Comprehensive scientific document review and analysis. Use when Claude needs to review scientific papers, reports, preprints, or other research documents for: (1) Identifying and evaluating claims and supporting evidence, (2) Assessing logical argumentation and experimental design, (3) Reviewing citation adequacy and suggesting additional references, (4) Determining document type and research contribution, (5) Checking technical accuracy and methodology, (6) Providing constructive feedback on presentation and clarity. Also handles language, grammar, and formatting review separately.

ユーザーインタビュー、要件ヒアリング、ステークホルダー聞き取り時に使用するスキル。オープンエンド質問、要求の深掘り、前提の明確化を通じて、ユーザーの真のニーズを引き出します。Anchors:• Interviewing Users (Steve Portigal) / 適用: インタビュー設計と実施 / 目的: バイアスを避け深い洞察を得る• Just Enough Research (Erika Hall) / 適用: 実践的なヒアリング / 目的: 限られた時間で最大の洞察を得る• Software Requirements (Karl Wiegers) / 適用: 要件分析と構造化 / 目的: 曖昧さを排除し完全性を確保• The Mom Test (Rob Fitzpatrick) / 適用: 過去の具体的行動の質問 / 目的: 仮定的な話を避け真の課題を発見Trigger:Use when conducting user interviews, requirements gathering, stakeholder hearing.Open-ended question design, ambiguous requirement clarification, hidden needs discovery, 5Why analysis.

This skill should be used when checking Hugo content for consistency issues, validating internal references, detecting duplicate content, verifying frontmatter completeness, and ensuring proper naming conventions. Use this skill to audit content quality, fix broken links, and maintain consistency across a Hugo site.

Automates AI briefing preparation and technology research. Use for regular updates on AI trends, tools, and models relevant to the job search.