{"id":"aaedbdca-6bec-445a-8c66-53ec5a5128bd","slug":"jellyjelly814-data-to-empirics","name":"data-to-empirics","description":"从已清洗数据出发，自主完成全套实证分析流程。涵盖数据审查、描述性统计、 主回归、稳健性检验、内生性检验、异质性分析、机制分析与中介效应。 支持 DiD、RDD、IV、OLS/面板回归、高维固定效应。 输出可运行代码 + 表格 + 实证分析报告。 Triggers: 实证分析, empirical analysis, 数据分析, 回归分析, 做实证, run empirics, data to empirics, 描述性统计, 稳健性检验, 内生性检验, 异质性分析, 机制分析, 中介效应, DiD, RDD, IV, panel regression","canonicalUrl":"https://www.xpersona.co/skill/jellyjelly814-data-to-empirics","sourceUrl":"https://github.com/jellyjelly814/data-to-empirics","homepage":null,"source":"GITHUB_OPENCLEW","vendor":{"slug":"jellyjelly814","label":"Jellyjelly814","url":"https://github.com/jellyjelly814/data-to-empirics"},"protocols":["OPENCLEW"],"capabilities":[],"trustScore":null,"trustConfidence":"unknown","artifactCount":0,"benchmarkCount":0,"lastRelease":null,"freshnessAt":"2026-04-15T00:18:43.538Z","freshnessLabel":"Apr 15, 2026","securityReviewed":true,"openapiReady":false,"stats":[{"label":"Trust score","value":"Unknown"},{"label":"Compatibility","value":"OpenClaw"},{"label":"Freshness","value":"Apr 15, 2026"},{"label":"Vendor","value":"Jellyjelly814"},{"label":"Artifacts","value":"0"},{"label":"Benchmarks","value":"0"},{"label":"Last release","value":"Unpublished"}],"factsPreview":[{"factKey":"docs_crawl","category":"integration","label":"Crawlable docs","value":"6 indexed pages on the official domain","href":"https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar","sourceUrl":"https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar","sourceType":"search_document","confidence":"medium","observedAt":"2026-04-15T05:03:46.393Z","isPublic":true},{"factKey":"vendor","category":"vendor","label":"Vendor","value":"Jellyjelly814","href":"https://github.com/jellyjelly814/data-to-empirics","sourceUrl":"https://github.com/jellyjelly814/data-to-empirics","sourceType":"profile","confidence":"medium","observedAt":"2026-04-15T00:18:43.902Z","isPublic":true},{"factKey":"protocols","category":"compatibility","label":"Protocol compatibility","value":"OpenClaw","href":"https://www.xpersona.co/api/v1/agents/jellyjelly814-data-to-empirics/contract","sourceUrl":"https://www.xpersona.co/api/v1/agents/jellyjelly814-data-to-empirics/contract","sourceType":"contract","confidence":"medium","observedAt":"2026-04-15T00:18:43.902Z","isPublic":true},{"factKey":"traction","category":"adoption","label":"Adoption signal","value":"1 GitHub stars","href":"https://github.com/jellyjelly814/data-to-empirics","sourceUrl":"https://github.com/jellyjelly814/data-to-empirics","sourceType":"profile","confidence":"medium","observedAt":"2026-04-15T00:18:43.902Z","isPublic":true},{"factKey":"handshake_status","category":"security","label":"Handshake status","value":"UNKNOWN","href":"https://www.xpersona.co/api/v1/agents/jellyjelly814-data-to-empirics/trust","sourceUrl":"https://www.xpersona.co/api/v1/agents/jellyjelly814-data-to-empirics/trust","sourceType":"trust","confidence":"medium","observedAt":null,"isPublic":true}],"highlights":["1 GitHub stars","Trust evidence available"],"agentCard":{"name":"data-to-empirics","description":"从已清洗数据出发，自主完成全套实证分析流程。涵盖数据审查、描述性统计、 主回归、稳健性检验、内生性检验、异质性分析、机制分析与中介效应。 支持 DiD、RDD、IV、OLS/面板回归、高维固定效应。 输出可运行代码 + 表格 + 实证分析报告。 Triggers: 实证分析, empirical analysis, 数据分析, 回归分析, 做实证, run empirics, data to empirics, 描述性统计, 稳健性检验, 内生性检验, 异质性分析, 机制分析, 中介效应, DiD, RDD, IV, panel regression","source":"GITHUB_OPENCLEW","sourceId":"github:1166798519","repository":"https://github.com/jellyjelly814/data-to-empirics","documentation":"https://www.xpersona.co/skill/jellyjelly814-data-to-empirics/agent/jellyjelly814-data-to-empirics","protocols":["OPENCLEW"],"languages":["typescript"],"install":{"command":"git clone https://github.com/jellyjelly814/data-to-empirics.git","ecosystem":"git"},"examples":[{"kind":"example","language":"text","snippet":"Stage 1: 初始化 → Stage 2: 数据审查 → Stage 3: 描述性统计\n→ Stage 4: 主回归 → Stage 5: 稳健性 + 内生性检验\n→ Stage 6: 异质性分析 → Stage 7: 机制分析 + 中介效应\n→ [输出] 实证分析报告"},{"kind":"example","language":"python","snippet":"import json, os\nfrom datetime import datetime, timezone\nprogress_path = os.path.join(project_dir, \"progress.json\")\nwith open(progress_path) as f:\n    progress = json.load(f)\nnow = datetime.now(timezone.utc).isoformat()\nprogress[\"stages\"][\"stage_N\"] = {\"finished_at\": now, \"status\": \"completed\"}\nprogress[\"current_stage\"] = N + 1\nwith open(progress_path, \"w\") as f:\n    json.dump(progress, f, indent=2, ensure_ascii=False)"}]}}