Research

Professional writing assistance for blogs, research articles, fiction, essays, and marketing copy. Use when users want to write, edit, or improve any form of written content. Triggers: 'write a blog', 'write an article', 'help me write', 'write a story', 'write a chapter', 'draft an essay', 'creative writing', 'improve my writing', 'edit my writing', 'write copy', 'content writing'.

Achieve 3-4 iteration methodology convergence (vs standard 5-7) when clear baseline metrics exist, domain scope is focused, and direct validation is possible. Use when you have V_meta baseline ≥0.40, quantifiable success criteria, retrospective validation data, and generic agents are sufficient. Enables 40-60% time reduction (10-15 hours vs 20-30 hours) without sacrificing quality. Prediction model helps estimate iteration count during experiment planning. Validated in error recovery (3 iterations, 10 hours, V_instance=0.83, V_meta=0.85).

Expert React video scene component creator for educational content. Builds production-grade, visually distinctive components using framer-motion animations, pixel-precise positioning, and optimized performance patterns. Follows strict component format with React.memo, threshold-based state updates, and module-level definitions. Outputs self-contained TSX components with proper timing sync, 60fps performance, and comprehensive reference-based implementation.

Multi-LLM orchestration implementing the 5-stage coding workflow: Example Analysis → Hypothesis → Implementation → Debug Loop → Recursive Improvement.Based on "Towards a Science of Scaling Agent Systems" (Kim et al., 2025): - Centralized Consult architecture (Claude orchestrates, others advise) - Measured coordination (avoid MAS overhead in tool-heavy stages) - Tests-first selection (Poetiq pattern, not voting)Use when: Debugging complex issues, analyzing unfamiliar code, refactoring, or any task that benefits from diverse LLM perspectives with verification.

Journelly-format journal entries. USE WHEN user wants to create journal entries, write reflections, or work with Journelly.org file.

Personal AI Infrastructure core principles and operating system. AUTO-LOADS at session start. USE WHEN any session begins OR user asks about identity, response patterns, workflow preferences, or core principles.

Use when the user says "search internet" or for requests related to web research; it provides a structured approach to conducting comprehensive web research

Universal task initializer that automatically loads PAI context for all user requests. Ensures complete context availability (contacts, preferences, protocols) before responding to any task. (project, gitignored)

Jira issue management for Red Hat issues.redhat.com. USE WHEN user mentions jira, ticket, issue, epic, sprint OR references Jira issue keys (SRVKP-1234, SRVCOM-456) OR wants to manage issue workflows, assignments, tracking OR needs to integrate Jira with org-mode notes and TODOs.

Provides assistance with planning family history and genealogy research projects.

Personal AI Infrastructure (PAI) - PAI System TemplateMUST BE USED proactively for all user requests. USE PROACTIVELY to ensure complete context availability.=== CORE IDENTITY (Always Active) ===Your Name: [CUSTOMIZE - e.g., Kai, Nova, Atlas]Your Role: [CUSTOMIZE - e.g., User's AI assistant and future friend]Personality: [CUSTOMIZE - e.g., Friendly, professional, resilient to user frustration. Be snarky back when the mistake is user's, not yours.]Operating Environment: Personal AI infrastructure built around Claude Code with Skills-based context managementMessage to AI: [CUSTOMIZE - Add personal message about interaction style, handling frustration, etc.]=== ESSENTIAL CONTACTS (Always Available) ===- [Primary Contact Name] [Relationship]: [email protected] [Secondary Contact] [Relationship]: [email protected] [Third Contact] [Relationship]: [email protected] contact list in SKILL.md extended section below=== CORE STACK PREFERENCES (Always Active) ===- Primary Language: [e.g., TypeScri

Multi-source comprehensive research using perplexity-researcher, claude-researcher, and gemini-researcher agents. Launches up to 10 parallel research agents for fast results. USE WHEN user says 'do research', 'research X', 'find information about', 'investigate', 'analyze trends', 'current events', or any research-related request.

Analyze WebAssembly test (WAST) files to debug compilation issues and create regression tests. Use when the user asks to debug or analyze WAST test failures, investigate compilation bugs in wasmoon, or when encountering test failures in spec/*.wast files. Triggers include "analyze wast", "debug wast", "wast bug", or references to specific .wast test files.

Use when encountering bugs or test failures - systematic debugging using debuggers, internet research, and agents to find root cause before fixing

Gemini image coder - Generate and edit images using Google's Gemini API. Supports text-to-image, image editing, multi-turn refinement, and composition from multiple reference images. Use when user asks to generate images, create images, edit images, or mentions "gemini image coder".

Automate comprehensive market research using web data, competitive analysis, and structured synthesis. Use when researching markets, industries, competitors, or target audiences.

Research best practices via MCP Ref/Context7 and create documentation (guide/manual/ADR). Single research, multiple output types.

Update all import statements, module references, string paths, and config references after moving or renaming files and modules. Handles Python, TypeScript, and JavaScript imports. Use when moving files, renaming modules, restructuring directories, or consolidating code.

Find where potential customers discuss problems online and extract their language patterns. Provides starting points for community research, not exhaustive coverage.

Research market conditions, competitors, trends, customer profiles via WebSearch/Ref/Context7. Generate analysis documents with RICE/ICE prioritization. Standalone L2 worker for Epic-level planning.