Research

事業仮説を支える一次/二次情報を整理し、意思決定に足る「根拠」「不確実性」「次の調査」を可視化する。でたらめな引用や推測の断言を避け、出典の実在を重視する。

Convert markdown documents to professional, retro LaTeX-style PDFs with academic formatting, clickable TOC, and proper citations.

Comprehensive cryptocurrency market research and analysis using specialized AI agents. Analyzes market data, price trends, news sentiment, technical indicators, macro correlations, and investment opportunities. Use when researching cryptocurrencies, analyzing crypto markets, evaluating digital assets, or investigating blockchain projects like Bitcoin, Ethereum, Solana, etc.

Proactively include clickable links when referencing entities (persons, conversations, messages). Makes responses actionable.

Hashnode GraphQL API documentation for creating, managing, and querying blogs, posts, publications, and user data on the Hashnode platform

Create API reference documentation from docstrings. Use when documenting public module interfaces.

Execute the complete experimental workflow - model optimization followed by evaluation - for all runs in a scaffolded experiment. Use after scaffold-experiment to submit jobs to SLURM.

Execute evidence-backed GitHub PR reviews with severity tagging, references, and merge-blocking guidance.

Coordinate research-focused testing and quality validation with clear constraints, gates, and confidence ceilings.

고객 여정 분석을 기반으로 핵심 문제 가설을 정의합니다. 테스트 가능한 문제 진술을 공식화할 때 사용하세요.

Use when synthesizing information from multiple sources (literature review, stakeholder feedback, research findings, data from different systems), creating or evaluating analogies for explanation or problem-solving (cross-domain transfer, "X is like Y", structural mapping), combining conflicting viewpoints into unified framework, identifying patterns across disparate sources, finding creative solutions by transferring principles from one domain to another, testing whether analogies hold (surface vs deep similarities), or when user mentions "synthesize", "combine sources", "analogy", "like", "similar to", "transfer from", "integrate findings", "what's it analogous to".

Determine the true user intent, constraints, and success criteria for research tasks with explicit confidence ceilings.

End-to-end orchestration of the deep research lifecycle across discovery, experimentation, and production gates.

Synthesize multiple sources into coherent narratives with explicit evidence tracking and confidence ceilings.

Generate research visuals (figures, diagrams) with constraints, evidence alignment, and confidence ceilings.

Use when exploring alternative scenarios, testing assumptions through "what if" questions, understanding causal relationships, conducting pre-mortem analysis, stress testing decisions, or when user mentions counterfactuals, hypothetical scenarios, thought experiments, alternative futures, what-if analysis, or needs to challenge assumptions and explore possibilities.

Use when testing ideas cheaply before building (pretotyping with fake doors, concierge MVPs, paper prototypes) to validate desirability/feasibility, choosing appropriate prototype fidelity (paper/clickable/coded), running experiments to test assumptions (demand, pricing, workflow), or when user mentions prototype, MVP, fake door test, concierge, Wizard of Oz, landing page test, smoke test, or asks "how can we validate this idea before building?".

Library documentation via Context7. Use for API references, code examples, framework docs.

Use when verifying claims before decisions, fact-checking statements against sources, conducting due diligence on vendor/competitor assertions, evaluating conflicting evidence, triangulating source credibility, assessing research validity for literature reviews, investigating misinformation, rating evidence strength (primary vs secondary), identifying knowledge gaps, or when user mentions "fact-check", "verify this", "is this true", "evaluate sources", "conflicting evidence", or "due diligence".

Explore open-source repositories, analyze implementation details of libraries/frameworks, and research official documentation. Use when you need to understand how features are implemented in popular open-source projects.