Results for “evidence-based-research”

Evidence-based health research using tiered trusted sources with GRADE-inspired evidence ratings. Integrates Apple Health data for personalized context. Use when user asks health, nutrition, exercise, sleep, or wellness questions.

Evidence-first current-state research workflow for ECC. Use when the user wants fresh facts, comparisons, enrichment, or a recommendation built from current public evidence and any supplied local context.

Turn research inputs into concise evidence, patterns, confidence levels, and product decisions.

Runs evidence-first current-state research, comparing options and enriching people or companies, then reports with explicit evidence boundaries.

Select evidence-based study strategies matched to material type, learning goal, and student habits. Use when advising students on revision techniques, homework, or independent study approaches.

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.

research-synthesis

Run evidence-first research, web/source search, Exa search, iterative retrieval, and research-before-coding workflows. Use when prompts ask for current facts, source-backed recommendations, market or company research, code/library discovery, query refinement, cited synthesis, deep research, or the old deep-research/research-ops/exa-search/iterative-retrieval/search-first skills.

Turn a refined research proposal or method idea into a detailed, claim-driven experiment roadmap. Use after `research-refine`, or when the user asks for a detailed experiment plan, ablation matrix, evaluation protocol, run order, compute budget, or paper-ready validation that supports the core problem, novelty, simplicity, and any LLM / VLM / Diffusion / RL-based contribution.

Transparent, rigorous research with full methodology — not a black-box API wrapper. Conducts exhaustive investigation through mandated 2-cycle research per theme, APA 7th citations, evidence hierarchy, and 3 user checkpoints. Self-contained using native OpenClaw tools (web_search, web_fetch, sessions_spawn). Use for literature reviews, competitive intelligence, or any research requiring academic rigor and reproducibility.

基于已摄取文献和本地数据，生成经管实证研究设计：问题、机制、变量、模型、识别、机制、异质性、稳健性

Route research prompts to evidence, retrieval, scraping, data, market, or scientific research skills. Use when prompts mention deep research, current facts, citations, Exa, iterative retrieval, search-first, scraping, data pipelines, PubMed, USPTO, gget, literature review, or scholar evaluation.

Systematic research methodology for formulating problems, building evidence-based arguments, and communicating findings in academic contexts. For scholarly writing, thesis development, and knowledge contribution. NOT for creative writing, journalistic reporting, or business analytics.

Semantic search, similar content discovery, and structured research using Exa API

以证据为先的ECC当前状态研究工作流程。当用户希望基于当前公开证据和提供的本地上下文获取最新事实、比较、丰富信息或建议时使用。

Scaffolds a program.md research program for autoresearch by auto-detecting codebase signals and interviewing for missing details.

Deep research on a topic using web search, docs, and codebase analysis

Perform semantic search, find similar content, and conduct structured research using the Exa API.

Researches VC funds and partners, providing thesis matching, portfolio analysis, and approach strategy for outreach.

Comprehensive results analysis for empirical research: generate publication-quality descriptive statistics and balance tables, interpret regression coefficients with economic magnitude and effect sizes, assess identification assumption diagnostics, and produce structured results memos. Use when asked to create summary statistics, Table 1, balance tests, interpret results, assess economic significance, or write results narratives.

Plan and synthesize product/user research with method rigor: select the right method for the goal, compute defensible sample sizes with confidence labels, and cluster coded observations into insights while flagging single-source anecdotes.

Claim-driven 实验设计：界定目标 claims → 设计实验块（baseline/validation/ablation/robustness）→ 构建执行顺序 → 可选 Review LLM review → 写入 wiki

Research-backed evolution advice for your knowledge system. Analyzes health reports, friction patterns, and derivation history to propose specific changes with research justification. Never auto-implements — proposals require your approval.

根据研究者提供的**研究计划书（Research Proposal）**执行基于**外国（美国/欧盟/英国/日本/跨国）制度环境**的公司金融类实证研究全流程。**启动后第一件事：根据计划书的主题、识别策略、贡献边际与样本范围，从外国 CF 顶刊池（AER/QJE/JPE/JF/JFE/RFS/JFQA/JAR/JAE/MS/JCF/JBF 等 25+ 期刊）中推荐 5 本最匹配的目标期刊（[J1]–[J5]），等待研究者明确选定一本；该期刊决定 main.tex 的 bibliographystyle、Section 骨架、Introduction 风格与表注规范**。然后用 Python 完成数据清洗、描述性统计、基准回归、内生性检验（IV/2SLS、DML）、平行趋势、异质性、机制、稳健性检验与图表绘制。LaTeX 表格和图像严格遵循 template/ 示例格式，研究逻辑与排版严格遵循 rule/ 下的《通用实证研究逻辑与规范总结》与《回归表写作规范总结》。数据集与政策集从 asset/ 中按计划书中的关键词检索（WRDS / NBER/Fed releases / FRED / 全球宏观库）。**当计划书预期的实证结果无法实现时（系数不显著、平行趋势不通过、IV 弱工具、机制不成立等），skill 自动切换备选方案直至完成研究项目**。最终交付物：Python 代码 + LaTeX 表格 + 图像（.pdf/.png）。触发条件：研究者提交研究计划书（含 X→Y 假设、识别策略、样本、政策冲击等）。

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

Orchestrate a full theory-first idea discovery pipeline. Use when the user wants the analysis counterpart of idea-discovery: literature context, proof-oriented idea generation, novelty checking, DeepSeek critique, and an analysis plan instead of an experiment-first workflow.

将一篇经管实证论文摄取为实证研究 wiki：论文卡片 + 变量 + 数据 + 模型 + 机制 + 识别 + 稳健性 + 异质性 + 表格线索

Design a practitioner inquiry cycle from research question through data collection to evidence-informed action. Use when starting action research, teacher-led investigation, or professional inquiry.

Stateful validator-gated research loop with native-hook persistence

Design and evaluate paid-ad experiments with hypotheses, randomization, sample-size calculations, guardrails, and decision rules for A/B and split tests.

Generate structured research briefs from RSS feeds and web sources on any topic. Synthesizes multiple sources into actionable analysis with key findings, data points, expert perspectives, and content angles.

Turn accepted search evidence into an intent, competitor, and information-gain brief.