{ "schemaVersion": "1.0", "item": { "slug": "interview-analysis", "name": "Interview Analysis", "source": "tencent", "type": "skill", "category": "数据分析", "sourceUrl": "https://clawhub.ai/mikonos/interview-analysis", "canonicalUrl": "https://clawhub.ai/mikonos/interview-analysis", "targetPlatform": "OpenClaw" }, "install": { "downloadMode": "redirect", "downloadUrl": "/downloads/interview-analysis", "sourceDownloadUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=interview-analysis", "sourcePlatform": "tencent", "targetPlatform": "OpenClaw", "installMethod": "Manual import", "extraction": "Extract archive", "prerequisites": [ "OpenClaw" ], "packageFormat": "ZIP package", "includedAssets": [ "README.md", "SKILL.md", "templates/evaluation_template.md", "templates/insight_template.md", "templates/profile_template.md", "templates/structure_note_template.md" ], "primaryDoc": "SKILL.md", "quickSetup": [ "Download the package from Yavira.", "Extract the archive and review SKILL.md first.", "Import or place the package into your OpenClaw setup." ], "agentAssist": { "summary": "Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.", "steps": [ "Download the package from Yavira.", "Extract it into a folder your agent can access.", "Paste one of the prompts below and point your agent at the extracted folder." ], "prompts": [ { "label": "New install", "body": "I downloaded a skill package from Yavira. 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Read SKILL.md from the extracted folder and install it by following the included instructions. Then review README.md for any prerequisites, environment setup, or post-install checks. Tell me what you changed and call out any manual steps you could not complete." }, { "label": "Upgrade existing", "body": "I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Then review README.md for any prerequisites, environment setup, or post-install checks. Summarize what changed and any follow-up checks I should run." } ] }, "documentation": { "source": "clawhub", "primaryDoc": "SKILL.md", "sections": [ { "title": "Interview Analysis Skill", "body": "Core Mission: Transform interview transcripts into deep insights.\nCore Logic: Don't listen to what candidates \"say\" (Methodology Recitation), observe what they've \"done\" (Battle Scars) and \"how they think\" (First Principles)." }, { "title": "Core Principle", "body": "Based on role type and evaluation dimensions, automatically select the best minds combination for that domain:\n\nThree-Step Expert Selection:\n\nIdentify core competency domain: Product/Engineering/Operations/Design/Sales/Data Science/...\nMatch top domain thinkers: Recognized methodology masters or practitioners in the field\nCombine hiring experts: Geoff Smart (fact-checking) + Lou Adler (competency validation)" }, { "title": "Common Role-Expert Mapping (Non-Exhaustive)", "body": "Role TypeDomain Expert (Methodology)Hiring Expert (Validation)RationaleProduct ManagerMarty Cagan / Julie ZhuoGeoff SmartProduct Sense + Fact CheckSoftware EngineerLinus Torvalds / John CarmackLou AdlerEngineering Judgment + Results ValidationGrowth HackerSean Ellis / Brian BalfourGeoff SmartGrowth Methodology + Metrics VerificationUX DesignerDon Norman / Jony IveLou AdlerUX Principles + Portfolio ValidationData ScientistAndrew Ng / DJ PatilGeoff SmartTechnical Depth + Project VerificationOperationsSheryl Sandberg / Reid HoffmanLou AdlerScale Operations + Results FocusSales/BDAaron Ross / Jill KonrathGeoff SmartSales Methodology + Performance Verification\n\n[!IMPORTANT]\nFlexibility Principle: The table above is for reference only. Flexibly select the most appropriate expert combination based on specific role and candidate background.\nEncourage Innovation: If you believe a non-mainstream expert is better suited to evaluate this candidate, make that choice and explain your rationale.\nCore Question: \"Who can best identify imposters in this role? Whose framework best validates core competencies?\"" }, { "title": "Step 1: Fact Reconstruction & Red Flag Scan", "body": "Timeline Reconstruction: Connect experiences scattered across multiple interview rounds, checking for logical gaps.\nConsistency Verification: Compare different versions of the same story told to different interviewers (e.g., reasons for leaving, project failures).\nRed Flag Annotation: Mark all vague titles (e.g., SPM), exaggerated data, and attribution fallacies (\"it was all market/technology's fault\")." }, { "title": "Step 2: Deep Decoding - STAR Episodes", "body": "Tactic: Select 1-2 core cases (e.g., startup project, most challenging project) for microscopic analysis.\nTruth Extraction:\n\nMethodology Check: Is the candidate reciting SOPs (MECE, SWOT) or applying first principles?\nSolution Bias Check: Did they jump straight to \"add features,\" or first conduct \"value validation\"?\nTechnical Boundary Check: For technical challenges, did they \"deflect blame\" or \"anticipate\"?" }, { "title": "Step 3: Interviewer Meta-Analysis", "body": "Subject: Evaluate interviewer (you/colleagues) performance.\nDimensions:\n\nDepth: Did they probe at critical moments? Or let it pass?\nBias: Did they draw conclusions too early or ask leading questions?\nBar: Did they maintain A Player standards?" }, { "title": "Step 4: Card-based Output (Zettelkasten Output)", "body": "Generate Markdown cards using the following standard templates, saved to people/{candidate_name}/analysis/. Be sure to read template content before filling in analysis results.\n\nProfile (Comprehensive Portrait):\n\nTemplate path: templates/profile_template.md\nPurpose: Fact checking, red flag scanning, core competency assessment.\n\n\nInsight (Deep Analysis):\n\nTemplate path: templates/insight_template.md\nPurpose: Deep dive into specific domains (e.g., AI Capability, Product Strategy).\n\n\nMeta-Analysis (Interviewer Review):\n\nTemplate path: templates/evaluation_template.md\nPurpose: Evaluate interviewer performance and organizational recommendations.\n\n\nStructure Note (Hub Document):\n\nTemplate path: templates/structure_note_template.md\nPurpose: Serves as hub connecting all analysis cards above, forming decision closure." }, { "title": "3. Usage Examples", "body": "\"Analyze Li Yashuang's three interview rounds, focusing on AI capabilities.\"\n\"Review this interview to see where we interviewers did well and where we missed opportunities.\"\n\"Use Marty Cagan's perspective to analyze this candidate's product thinking.\"" } ], "body": "Interview Analysis Skill\n\nCore Mission: Transform interview transcripts into deep insights. Core Logic: Don't listen to what candidates \"say\" (Methodology Recitation), observe what they've \"done\" (Battle Scars) and \"how they think\" (First Principles).\n\n1. Dynamic Expert Activation (Expert Routing)\nCore Principle\n\nBased on role type and evaluation dimensions, automatically select the best minds combination for that domain:\n\nThree-Step Expert Selection:\n\nIdentify core competency domain: Product/Engineering/Operations/Design/Sales/Data Science/...\nMatch top domain thinkers: Recognized methodology masters or practitioners in the field\nCombine hiring experts: Geoff Smart (fact-checking) + Lou Adler (competency validation)\nCommon Role-Expert Mapping (Non-Exhaustive)\nRole Type\tDomain Expert (Methodology)\tHiring Expert (Validation)\tRationale\nProduct Manager\tMarty Cagan / Julie Zhuo\tGeoff Smart\tProduct Sense + Fact Check\nSoftware Engineer\tLinus Torvalds / John Carmack\tLou Adler\tEngineering Judgment + Results Validation\nGrowth Hacker\tSean Ellis / Brian Balfour\tGeoff Smart\tGrowth Methodology + Metrics Verification\nUX Designer\tDon Norman / Jony Ive\tLou Adler\tUX Principles + Portfolio Validation\nData Scientist\tAndrew Ng / DJ Patil\tGeoff Smart\tTechnical Depth + Project Verification\nOperations\tSheryl Sandberg / Reid Hoffman\tLou Adler\tScale Operations + Results Focus\nSales/BD\tAaron Ross / Jill Konrath\tGeoff Smart\tSales Methodology + Performance Verification\n\n[!IMPORTANT] Flexibility Principle: The table above is for reference only. Flexibly select the most appropriate expert combination based on specific role and candidate background.\n\nEncourage Innovation: If you believe a non-mainstream expert is better suited to evaluate this candidate, make that choice and explain your rationale.\n\nCore Question: \"Who can best identify imposters in this role? Whose framework best validates core competencies?\"\n\n2. Execution Workflow\nStep 1: Fact Reconstruction & Red Flag Scan\nTimeline Reconstruction: Connect experiences scattered across multiple interview rounds, checking for logical gaps.\nConsistency Verification: Compare different versions of the same story told to different interviewers (e.g., reasons for leaving, project failures).\nRed Flag Annotation: Mark all vague titles (e.g., SPM), exaggerated data, and attribution fallacies (\"it was all market/technology's fault\").\nStep 2: Deep Decoding - STAR Episodes\nTactic: Select 1-2 core cases (e.g., startup project, most challenging project) for microscopic analysis.\nTruth Extraction:\nMethodology Check: Is the candidate reciting SOPs (MECE, SWOT) or applying first principles?\nSolution Bias Check: Did they jump straight to \"add features,\" or first conduct \"value validation\"?\nTechnical Boundary Check: For technical challenges, did they \"deflect blame\" or \"anticipate\"?\nStep 3: Interviewer Meta-Analysis\nSubject: Evaluate interviewer (you/colleagues) performance.\nDimensions:\nDepth: Did they probe at critical moments? Or let it pass?\nBias: Did they draw conclusions too early or ask leading questions?\nBar: Did they maintain A Player standards?\nStep 4: Card-based Output (Zettelkasten Output)\n\nGenerate Markdown cards using the following standard templates, saved to people/{candidate_name}/analysis/. Be sure to read template content before filling in analysis results.\n\nProfile (Comprehensive Portrait):\nTemplate path: templates/profile_template.md\nPurpose: Fact checking, red flag scanning, core competency assessment.\nInsight (Deep Analysis):\nTemplate path: templates/insight_template.md\nPurpose: Deep dive into specific domains (e.g., AI Capability, Product Strategy).\nMeta-Analysis (Interviewer Review):\nTemplate path: templates/evaluation_template.md\nPurpose: Evaluate interviewer performance and organizational recommendations.\nStructure Note (Hub Document):\nTemplate path: templates/structure_note_template.md\nPurpose: Serves as hub connecting all analysis cards above, forming decision closure.\n3. Usage Examples\n\"Analyze Li Yashuang's three interview rounds, focusing on AI capabilities.\"\n\"Review this interview to see where we interviewers did well and where we missed opportunities.\"\n\"Use Marty Cagan's perspective to analyze this candidate's product thinking.\"" }, "trust": { "sourceLabel": "tencent", "provenanceUrl": "https://clawhub.ai/mikonos/interview-analysis", "publisherUrl": "https://clawhub.ai/mikonos/interview-analysis", "owner": "mikonos", "version": "1.0.0", "license": null, "verificationStatus": "Indexed source record" }, "links": { "detailUrl": "https://openagent3.xyz/skills/interview-analysis", "downloadUrl": "https://openagent3.xyz/downloads/interview-analysis", "agentUrl": "https://openagent3.xyz/skills/interview-analysis/agent", "manifestUrl": "https://openagent3.xyz/skills/interview-analysis/agent.json", "briefUrl": "https://openagent3.xyz/skills/interview-analysis/agent.md" } }