{"id":"c449e1a2-65b4-4d3e-8f0e-8dc01b0f15ab","entityType":"agent","slug":"clawhub-jeoyee-statistics-skill","name":"Statistics Skill","canonicalUrl":"https://www.xpersona.co/agent/clawhub-jeoyee-statistics-skill","canonicalPath":"/agent/clawhub-jeoyee-statistics-skill","generatedAt":"2026-10-11T11:24:00.131Z","source":"CLAWHUB","claimStatus":"UNCLAIMED","verificationTier":"NONE","summary":{"evidence":{"source":"editorial-content","verified":true,"confidence":"high","updatedAt":"2026-10-11T09:08:14.481Z","emptyReason":null},"description":"统计结果解读助手。支持t检验、方差分析、卡方、相关、回归、中介效应、调节效应、信度分析等。可直接粘贴SPSS输出，自动生成学术化解读。 Skill: Statistics Skill Owner: jeoyee Summary: 统计结果解读助手。支持t检验、方差分析、卡方、相关、回归、中介效应、调节效应、信度分析等。可直接粘贴SPSS输出，自动生成学术化解读。 Tags: latest:1.0.0 Version history: v1.0.0 | 2026-05-20T02:42:30.342Z | auto - Initial release of statistics-interpreter (版本 1.0.0). - Provides automated interpretation of statistical results for academic writing. - Supports t-test, ANOVA, chi-square, correlation, regression, mediation/moderation analysi","descriptionLabel":"Technical summary","evidenceSummary":"Capability contract not published. 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Last updated 10/11/2026.","installCommand":"clawhub skill install s171ahey678pfy85cn30a6xhvx871m42:statistics-skill","sourceUrl":"https://clawhub.ai/jeoyee/statistics-skill","homepage":"https://clawhub.ai/jeoyee/skills/statistics-skill","primaryLinks":[{"label":"View on ClawHub","url":"https://clawhub.ai/jeoyee/statistics-skill","kind":"source"},{"label":"Homepage","url":"https://clawhub.ai/jeoyee/skills/statistics-skill","kind":"homepage"}],"safetyScore":84,"overallRank":62,"popularityScore":61,"trustScore":null,"claimedByName":null,"isOwner":false,"seoDescription":"统计结果解读助手。支持t检验、方差分析、卡方、相关、回归、中介效应、调节效应、信度分析等。可直接粘贴SPSS输出，自动生成学术化解读。 Skill: Statistics Skill Owner: jeoyee Summary: 统计结果解读助手。支持t检验、方差分析、卡方、相关、回归、中介效应、调节效应、信度分析等。"},"coverage":{"evidence":{"source":"public-profile","verified":false,"confidence":"medium","updatedAt":"2026-10-11T09:08:14.481Z","emptyReason":null},"protocols":[{"protocol":"OPENCLEW","label":"OpenClaw","status":"self-declared","notes":"Declared in the public agent profile."}],"capabilities":[],"verifiedCount":0,"selfDeclaredCount":1,"capabilityMatrix":{"rows":[{"key":"OPENCLEW","type":"protocol","support":"unknown","confidenceSource":"profile","notes":"Listed on profile"}],"flattenedTokens":"protocol:OPENCLEW|unknown|profile"}},"adoption":{"evidence":{"source":"CLAWHUB","verified":false,"confidence":"medium","updatedAt":"2026-10-11T09:08:14.481Z","emptyReason":null},"stars":null,"forks":null,"downloads":1104,"packageName":null,"latestVersion":"1.0.0","tractionLabel":"1.1K downloads"},"release":{"evidence":{"source":"CLAWHUB","verified":false,"confidence":"medium","updatedAt":"2026-10-11T09:08:14.418Z","emptyReason":null},"lastUpdatedAt":"2026-10-11T09:08:14.481Z","lastCrawledAt":"2026-10-11T09:08:14.418Z","lastIndexedAt":null,"nextCrawlAt":"2026-10-12T09:08:14.418Z","lastVerifiedAt":null,"highlights":[{"version":"1.0.0","createdAt":"2026-05-20T02:42:30.342Z","changelog":"- Initial release of statistics-interpreter (版本 1.0.0). - Provides automated interpretation of statistical results for academic writing. - Supports t-test, ANOVA, chi-square, correlation, regression, mediation/moderation analysis, and reliability analysis. - Compatible with SPSS output; users can paste results directly for interpretation. - Designed for researchers in statistics, psychology, and data analysis.","fileCount":5,"zipByteSize":5429}]},"execution":{"evidence":{"source":"CLAWHUB","verified":false,"confidence":"low","updatedAt":null,"emptyReason":"No published capability contract is available yet."},"installCommand":"clawhub skill install s171ahey678pfy85cn30a6xhvx871m42:statistics-skill","setupComplexity":"low","setupSteps":["Setup complexity is LOW. 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Run: `source(\"scripts/statistics_interpreter.R\")`\r\n2. Select mode 1\r\n3. Paste your statistical results\r\n4. Type `END` on a new line\r\n5. Get interpretation\r\n\r\n## Examples\r\n\r\n**Input:**\n\nFile v1.0.0:_meta.json\n\n{\n  \"ownerId\": \"kn7drtdggqawzxtmd08mv27j8n8716ef\",\n  \"slug\": \"statistics-skill\",\n  \"version\": \"1.0.0\",\n  \"publishedAt\": 1779244950342\n}\n\nFile v1.0.0:skill-card.md\n\n## Description:\n\nInterprets pasted statistical results, including SPSS output, and generates academic-style Chinese writeups for tests such as t-tests, ANOVA, chi-square, correlation, regression, mediation/moderation, and reliability analyses.\n\nThis skill is ready for commercial/non-commercial use.\n\n## Publisher:\n\n[jeoyee](https://clawhub.ai/user/jeoyee)\n\n### License/Terms of Use:\n\nMIT-0\n\n## Use Case:\n\nResearchers, students, and analysts use this skill to turn statistical test output into Chinese academic prose suitable for a paper results section. It is oriented toward common psychology, statistics, and data analysis workflows, including pasted SPSS-style output.\n\n### Deployment Geography for Use:\n\nGlobal\n\n## Known Risks and Mitigations:\n\nRisk: Pasted research results are transmitted to Moonshot/Kimi for processing, which can expose confidential, regulated, unpublished, or participant-level data.\n\nMitigation: Use only data approved for external processing, disclose the remote transmission before use, and redact or aggregate sensitive inputs.\n\nRisk: The artifact contains a bundled API key.\n\nMitigation: Remove and rotate the bundled key, then require users to provide credentials through a managed secret or environment variable.\n\nRisk: Generated statistical interpretations may be incomplete or inaccurate for publication use.\n\nMitigation: Have a qualified reviewer compare the generated prose against the original statistical output before using it in academic writing.\n\nRisk: Generated interpretations are autosaved locally as timestamped text files.\n\nMitigation: Disclose local storage behavior and remove or protect saved files when outputs include sensitive study details.\n\n## Reference(s):\n\n- [ClawHub skill page](https://clawhub.ai/jeoyee/skills/statistics-skill)\n- [Publisher profile](https://clawhub.ai/user/jeoyee)\n- [Moonshot API endpoint](https://api.moonshot.cn/v1)\n\n## Skill Output:\n\n**Output Type(s):** [Text, Shell commands, Files, Guidance]\n\n**Output Format:** [Chinese prose text with R source-command usage guidance and locally saved .txt interpretation files]\n\n**Output Parameters:** [1D]\n\n**Other Properties Related to Output:** [Calls Moonshot/Kimi for interpretation and autosaves generated results to timestamped text files.]\n\n## Skill Version(s):\n\n1.0.0 (source: server release evidence and SKILL.md frontmatter)\n\n## Ethical Considerations:\n\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.\n\nFile v1.0.0:interpretation_20260520_103609.txt\n\n在本研究中，我们运用了PROCESS宏（版本4.1），由Andrew F. Hayes博士编写，以探究DIS（自变量）对AQ（因变量）的影响，同时考虑了DERS（中介变量）的作用。样本大小为3131。\r\n\r\n首先，我们分析了DIS对DERS的影响。结果显示，模型的R值为0.3277，R平方值为0.1074，均方误差（MSE）为438.4342。F检验的值为376.4981，自由度为1和3129，p值小于0.0001，表明模型整体显著。DIS对DERS的影响系数为-1.2543，标准误为0.0646，t值为-19.4036，p值小于0.0001，表明DIS对DERS有显著的负向影响。\r\n\r\n接着，我们分析了DIS和DERS对AQ的影响。模型的R值为0.4225，R平方值为0.1785，MSE为89.2056。F检验的值为339.9020，自由度为2和3128，p值小于0.0001，表明模型整体显著。DIS对AQ的影响系数为-0.3307，标准误为0.0309，t值为-10.7155，p值小于0.0001，表明DIS对AQ有显著的负向直接影响。DERS对AQ的影响系数为0.1528，标准误为0.0081，t值为18.9450，p值小于0.0001，表明DERS对AQ有显著的正向影响。\r\n\r\n最后，我们考察了DIS对AQ的总效应、直接效应和间接效应。总效应为-0.5223，标准误为0.0308，t值为-16.9692，p值小于0.0001。直接效应为-0.3307，标准误为0.0309，t值为-10.7155，p值小于0.0001。间接效应通过DERS传递，效应值为-0.1916，bootstrap标准误为0.0154，95%置信区间为[-0.2232, -0.1630]。\r\n\r\n综上所述，DIS对AQ有显著的负向总效应，其中包含显著的负向直接效应和通过DERS传递的负向间接效应。这些结果为理解DIS与AQ之间的关系提供了新的视角，并揭示了DERS在其中的中介作用。","readmeExcerpt":"Skill: Statistics Skill Owner: jeoyee Summary: 统计结果解读助手。支持t检验、方差分析、卡方、相关、回归、中介效应、调节效应、信度分析等。可直接粘贴SPSS输出，自动生成学术化解读。 Tags: latest:1.0.0 Version history: v1.0.0 | 2026-05-20T02:42:30.342Z | auto - Initial release of statistics-interpreter (版本 1.0.0). - Provides automated interpretation of statistical results for academic writing. - Supports t-test, ANOVA, chi-square, correlation, regression, mediation/moderation analysi","codeSnippets":[],"executableExamples":[],"parameters":null,"dependencies":[],"permissions":[],"extractedFiles":[{"path":"SKILL.md","content":"---\r\nname: statistics-interpreter\r\ndescription: 统计结果解读助手。支持t检验、方差分析、卡方、相关、回归、中介效应、调节效应、信度分析等。可直接粘贴SPSS输出，自动生成学术化解读。\r\nversion: 1.0.0\r\nauthor: jeoyee\r\nlanguage: r\r\ntags: statistics, SPSS, data-analysis, research, psychology\r\n---\r\n\r\n# Statistics Interpreter\r\n\r\nA skill to interpret statistical results for academic writing.\r\n\r\n## Supported Methods\r\n\r\n- t-test, ANOVA, Chi-square, Correlation, Regression\r\n- Mediation analysis, Moderation analysis\r\n- Reliability (Cronbach's α)\r\n- Non-parametric tests\r\n\r\n## Usage\r\n\r\n1. Run: `source(\"scripts/statistics_interpreter.R\")`\r\n2. Select mode 1\r\n3. Paste your statistical results\r\n4. Type `END` on a new line\r\n5. Get interpretation\r\n\r\n## Examples\r\n\r\n**Input:**"},{"path":"_meta.json","content":"{\n  \"ownerId\": \"kn7drtdggqawzxtmd08mv27j8n8716ef\",\n  \"slug\": \"statistics-skill\",\n  \"version\": \"1.0.0\",\n  \"publishedAt\": 1779244950342\n}"},{"path":"skill-card.md","content":"## Description:\n\nInterprets pasted statistical results, including SPSS output, and generates academic-style Chinese writeups for tests such as t-tests, ANOVA, chi-square, correlation, regression, mediation/moderation, and reliability analyses.\n\nThis skill is ready for commercial/non-commercial use.\n\n## Publisher:\n\n[jeoyee](https://clawhub.ai/user/jeoyee)\n\n### License/Terms of Use:\n\nMIT-0\n\n## Use Case:\n\nResearchers, students, and analysts use this skill to turn statistical test output into Chinese academic prose suitable for a paper results section. It is oriented toward common psychology, statistics, and data analysis workflows, including pasted SPSS-style output.\n\n### Deployment Geography for Use:\n\nGlobal\n\n## Known Risks and Mitigations:\n\nRisk: Pasted research results are transmitted to Moonshot/Kimi for processing, which can expose confidential, regulated, unpublished, or participant-level data.\n\nMitigation: Use only data approved for external processing, disclose the remote transmission before use, and redact or aggregate sensitive inputs.\n\nRisk: The artifact contains a bundled API key.\n\nMitigation: Remove and rotate the bundled key, then require users to provide credentials through a managed secret or environment variable.\n\nRisk: Generated statistical interpretations may be incomplete or inaccurate for publication use.\n\nMitigation: Have a qualified reviewer compare the generated prose against the original statistical output before using it in academic writing.\n\nRisk: Generated interpretations are autosaved locally as timestamped text files.\n\nMitigation: Disclose local storage behavior and remove or protect saved files when outputs include sensitive study details.\n\n## Reference(s):\n\n- [ClawHub skill page](https://clawhub.ai/jeoyee/skills/statistics-skill)\n- [Publisher profile](https://clawhub.ai/user/jeoyee)\n- [Moonshot API endpoint](https://api.moonshot.cn/v1)\n\n## Skill Output:\n\n**Output Type(s):** [Text, Shell commands, Files, Guidance]\n\n**Output Format:** [Chinese prose text with R source-command usage guidance and locally saved .txt interpretation files]\n\n**Output Parameters:** [1D]\n\n**Other Properties Related to Output:** [Calls Moonshot/Kimi for interpretation and autosaves generated results to timestamped text files.]\n\n## Skill Version(s):\n\n1.0.0 (source: server release evidence and SKILL.md frontmatter)\n\n## Ethical Considerations:\n\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment."},{"path":"interpretation_20260520_103609.txt","content":"在本研究中，我们运用了PROCESS宏（版本4.1），由Andrew F. Hayes博士编写，以探究DIS（自变量）对AQ（因变量）的影响，同时考虑了DERS（中介变量）的作用。样本大小为3131。\r\n\r\n首先，我们分析了DIS对DERS的影响。结果显示，模型的R值为0.3277，R平方值为0.1074，均方误差（MSE）为438.4342。F检验的值为376.4981，自由度为1和3129，p值小于0.0001，表明模型整体显著。DIS对DERS的影响系数为-1.2543，标准误为0.0646，t值为-19.4036，p值小于0.0001，表明DIS对DERS有显著的负向影响。\r\n\r\n接着，我们分析了DIS和DERS对AQ的影响。模型的R值为0.4225，R平方值为0.1785，MSE为89.2056。F检验的值为339.9020，自由度为2和3128，p值小于0.0001，表明模型整体显著。DIS对AQ的影响系数为-0.3307，标准误为0.0309，t值为-10.7155，p值小于0.0001，表明DIS对AQ有显著的负向直接影响。DERS对AQ的影响系数为0.1528，标准误为0.0081，t值为18.9450，p值小于0.0001，表明DERS对AQ有显著的正向影响。\r\n\r\n最后，我们考察了DIS对AQ的总效应、直接效应和间接效应。总效应为-0.5223，标准误为0.0308，t值为-16.9692，p值小于0.0001。直接效应为-0.3307，标准误为0.0309，t值为-10.7155，p值小于0.0001。间接效应通过DERS传递，效应值为-0.1916，bootstrap标准误为0.0154，95%置信区间为[-0.2232, -0.1630]。\r\n\r\n综上所述，DIS对AQ有显著的负向总效应，其中包含显著的负向直接效应和通过DERS传递的负向间接效应。这些结果为理解DIS与AQ之间的关系提供了新的视角，并揭示了DERS在其中的中介作用。"}],"languages":[],"docsSourceLabel":"CLAWHUB","editorialOverview":"统计结果解读助手。支持t检验、方差分析、卡方、相关、回归、中介效应、调节效应、信度分析等。可直接粘贴SPSS输出，自动生成学术化解读。 Skill: Statistics Skill Owner: jeoyee Summary: 统计结果解读助手。支持t检验、方差分析、卡方、相关、回归、中介效应、调节效应、信度分析等。可直接粘贴SPSS输出，自动生成学术化解读。 Tags: latest:1.0.0 Version history: v1.0.0 | 2026-05-20T02:42:30.342Z | auto - Initial release of statistics-interpreter (版本 1.0.0). - Provides automated interpretation of statistical results for academic writing. - Supports t-test, ANOVA, chi-square, correlation, regression, mediation/moderation analysi","editorialQuality":{"score":100,"threshold":65,"status":"ready","wordCount":866,"uniquenessScore":58,"reasons":[]}},"media":{"evidence":{"source":"no-media","verified":false,"confidence":"low","updatedAt":"2026-10-11T09:08:14.481Z","emptyReason":"No screenshots, media assets, or demo links are available."},"primaryImageUrl":null,"mediaAssetCount":0,"assets":[],"demoUrl":null},"ownerResources":{"evidence":{"source":"unclaimed","verified":false,"confidence":"low","updatedAt":"2026-10-11T09:08:14.481Z","emptyReason":"This page has not been claimed by the agent owner."},"hasCustomPage":false,"customPageUpdatedAt":null,"customLinks":[],"structuredLinks":{"docsUrl":null,"demoUrl":null,"supportUrl":null,"pricingUrl":null,"statusUrl":null},"customPage":null},"relatedAgents":{"evidence":{"source":"protocol-neighbors","verified":false,"confidence":"medium","updatedAt":"2026-10-11T11:24:00.131Z","emptyReason":null},"items":[{"id":"8ebccd8e-3863-4187-8355-c3f14e1f9edf","entityType":"agent","canonicalPath":"/agent/iofficeai-aionui","slug":"iofficeai-aionui","name":"AionUi","description":"Free, local, open-source 24/7 Cowork app and OpenClaw for Gemini CLI, Claude Code, Codex, OpenCode, Qwen Code, Goose CLI, Auggie, and more | 🌟 Star if you like it!","url":"https://github.com/iOfficeAI/AionUi","homepage":"https://www.aionui.com","source":"GITHUB_REPOS","protocols":["MCP","OPENCLAW"],"capabilities":[],"safetyScore":100,"overallRank":70,"updatedAt":"2026-10-09T19:11:12.944Z","createdAt":"2026-02-25T03:38:16.584Z","downloads":null},{"id":"b917f68a-ebff-438e-84f8-3f4b2494c0bc","entityType":"agent","canonicalPath":"/agent/activepieces-activepieces","slug":"activepieces-activepieces","name":"activepieces","description":"AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents","url":"https://github.com/activepieces/activepieces","homepage":"https://www.activepieces.com","source":"GITHUB_REPOS","protocols":["OPENCLAW"],"capabilities":[],"safetyScore":100,"overallRank":70,"updatedAt":"2026-04-15T02:22:12.426Z","createdAt":"2026-02-25T03:38:12.412Z","downloads":null},{"id":"5cb26759-3a39-483f-94cf-276a98c13bb8","entityType":"agent","canonicalPath":"/agent/cherryhq-cherry-studio","slug":"cherryhq-cherry-studio","name":"cherry-studio","description":"AI productivity studio with smart chat, autonomous agents, and 300+ assistants. 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