Results for “design-research”

Interrogates research plans before evals or published claims, forcing explicit null hypotheses, confound checks, and data verification across four review waves.

Design a diary study plan with prompts, duration, participant criteria, and analysis framework to understand user behavior over time in natural contexts.

Conducts end-to-end user research, from study design through behavioral insight synthesis, using frameworks like Nielsen's Heuristics, SUS, and User Journey Mapping.

Generate data-driven user personas for UX research and product design. Usage: /persona generate [options]

Design surveys that collect reliable, unbiased quantitative data to validate hypotheses and measure user attitudes at scale.

Use when a research design spec exists and the user is ready to translate it into a concrete implementation plan with phased tasks, artifacts, and verification criteria. Produces a research execution plan organized in canonical research phases — collection, preparation, analysis, robustness, writing, submission.

Guides a structured interview and repository research to clarify feature requirements, classify scope, and produce context artifacts for approval before design.

Builds reusable specialized skills for creating research-paper figures from lawful source material, then uses those skills to design and render figures for target papers.

Perform intermediate-level optics design tasks including wave equation solving, behavior prediction, and physical modeling for research, industry, or education.

Traces design decisions and concepts through session history, handoffs, git, and artifacts, producing a chronological timeline report with citations.

Stays current on UI design patterns, tools, and frameworks by monitoring release notes and running targeted search queries.

Design prospective clinical studies by selecting and classifying endpoints, estimating sample size and power for two-arm designs, and scoring study plans for feasibility with phase-gate decisions.

Routes research queries to specialist skills or runs a fallback search-and-synthesize workflow, with deterministic classification and transparent routing decisions.

Design experiments and studies before data collection — choosing a design, randomizing, blocking, and laying out treatment combinations so results are interpretable.

Researches and recommends programming technologies, libraries, and architectural approaches with verified references from official documentation.

Research companies, industries, or competitor sets using web search and seven analytical lenses to produce structured intelligence for downstream product management tasks.

Generate and rank research ideas given a broad direction. Use when user says "找idea", "brainstorm ideas", "generate research ideas", "what can we work on", or wants to explore a research area for publishable directions.

Cognitive enhancement toolkit combining non-linear reasoning, mental models, and literate programming. Use for complex analysis, system design, debugging, deep learning, and research workflows.

Research the open web for enhancement opportunities (Layer 3 — Opus subagent with WebSearch + WebFetch). Topic-driven. Returns structured findings with hype tags + source URLs. Does NOT auto-implement.

Produces decision-oriented market research, competitive analysis, investor due diligence, and industry intelligence with source attribution.

VS-Enhanced Quantitative Design Consultant with Materials & Sampling Enhanced VS 3-Phase process: Avoids obvious experimental designs, proposes context-optimal quantitative strategies Absorbed C4 (Experimental Materials Developer) and D1 (Sampling Strategy Advisor) capabilities Use when: selecting quantitative research design, planning experimental/survey methodology, power analysis, developing materials, sampling Triggers: RCT, quasi-experimental, experimental design, survey design, power analysis, sample size, factorial design, materials, stimuli, sampling strategy

Design click and first-click tests to evaluate navigation clarity and information findability in user interfaces.

金融经济学实证论文计划书生成器。根据用户提供的研究方向，生成包含标题、假说、数据来源、实证策略、 预期结果表格、稳健性检验、异质性分析、机制检验等12个完整模块的研究计划书。 内置中国微观/宏观数据库（皮皮侠1599个数据集、马克数据377个数据集）和WRDS国际数据库索引， 自动匹配可用数据源。融合Edmans (2024) "Learnings From 1000 Rejections"的编辑视角作为质量护栏， 确保选题具有真正的边际贡献而非"just another determinant of Y"。 当用户提到以下任何情境时触发：写研究计划书、research proposal、论文开题、选题+计划、 帮我设计一个实证研究、empirical research design、我想研究X对Y的影响怎么做、 帮我找个能发表的选题、generate proposal、写一个可以投稿的研究方案、 研究设计、identification strategy、DID/RDD/IV研究设计。 即使用户只是描述了一个经济金融现象并想知道"能不能做成论文"，也应考虑使用此技能。

Design a usability test plan with tasks, success metrics, participant criteria, and facilitation guide for moderated or unmoderated sessions.

Creates a comprehensive end-to-end user journey map with stages, touchpoints, emotions, pain points, and opportunity areas for product design and UX analysis.

STATA code pattern library for empirical archival accounting research. Provides tested syntax from 126 peer-reviewed JAR (Journal of Accounting Research) replication files (2017-2025). Use when the user asks procedural questions like "How do I implement [method]?" or "Show me code for [technique]" — including: entropy balancing, propensity score matching (PSM), difference-in-differences (DiD), regression discontinuity (RDD), instrumental variables (IV), event studies (CAR/BHAR), survival analysis, Fama-MacBeth regressions, bootstrap, quantile regression, reghdfe/xtreg/areg, clustering standard errors, fixed effects, esttab/outreg2 table formatting, winsorization, leads/lags. Users can specify their variables (e.g., treatment, outcomes, controls) and receive adapted syntax. NOTE: This skill provides code patterns from published papers, not research design advice.

Use when a research note system needs architecture, when MOCs, frontmatter standards, and retrieval patterns must be designed for years of work, or when an existing vault has outgrown its structure and must migrate without breaking years of links.

Systematic strategic planning framework for philosophy and interdisciplinary academic papers targeting preprint platforms (PhilArchive, arXiv, PhilSci-Archive). Use when users want to: (1) plan a paper on a specific topic, (2) identify research gaps and assess originality, (3) develop optimized paper outlines, (4) prepare for preprint submission, or (5) understand platform requirements and writing standards. Triggered by phrases like 'plan a paper on,' 'help me design a paper about,' 'identify research gaps in,' 'is this idea original,' or when users need structured research planning. The skill guides through three phases: Platform Analysis (identifying target venue and studying sample papers), Theoretical Framework (AI-driven literature search and gap identification), and Outline Optimization (structured design with reviewer-perspective self-assessment). Each phase includes quality evaluation standards and validation checkpoints. Output: optimized detailed outline ready for systematic writing (use with acade

Evaluate scientific claims and evidence quality by assessing experimental design, identifying biases and confounders, and applying evidence grading frameworks like GRADE and Cochrane Risk of Bias.

Mega-composite — full greenfield feature development from idea to live. Chains research-and-decide (validate the idea + capture decision) → scope-and-execute (analysis + plan + implement) → design-build (if UI involved) → fix-the-suite (if tests need work) → merge-confidently → ship-it → knowledge-loop. The single command for "build feature X end-to-end."