{
  "schemaVersion": "1.0",
  "item": {
    "slug": "product-manager-toolkit",
    "name": "Product Manager Toolkit",
    "source": "tencent",
    "type": "skill",
    "category": "开发工具",
    "sourceUrl": "https://clawhub.ai/alirezarezvani/product-manager-toolkit",
    "canonicalUrl": "https://clawhub.ai/alirezarezvani/product-manager-toolkit",
    "targetPlatform": "OpenClaw"
  },
  "install": {
    "downloadMode": "redirect",
    "downloadUrl": "/downloads/product-manager-toolkit",
    "sourceDownloadUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=product-manager-toolkit",
    "sourcePlatform": "tencent",
    "targetPlatform": "OpenClaw",
    "installMethod": "Manual import",
    "extraction": "Extract archive",
    "prerequisites": [
      "OpenClaw"
    ],
    "packageFormat": "ZIP package",
    "includedAssets": [
      "SKILL.md",
      "references/frameworks.md",
      "references/input-output-examples.md",
      "references/prd_templates.md",
      "scripts/customer_interview_analyzer.py",
      "scripts/rice_prioritizer.py"
    ],
    "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. Read SKILL.md from the extracted folder and install it by following the included instructions. 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. Summarize what changed and any follow-up checks I should run."
        }
      ]
    },
    "sourceHealth": {
      "source": "tencent",
      "status": "healthy",
      "reason": "direct_download_ok",
      "recommendedAction": "download",
      "checkedAt": "2026-04-30T16:55:25.780Z",
      "expiresAt": "2026-05-07T16:55:25.780Z",
      "httpStatus": 200,
      "finalUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=network",
      "contentType": "application/zip",
      "probeMethod": "head",
      "details": {
        "probeUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=network",
        "contentDisposition": "attachment; filename=\"network-1.0.0.zip\"",
        "redirectLocation": null,
        "bodySnippet": null
      },
      "scope": "source",
      "summary": "Source download looks usable.",
      "detail": "Yavira can redirect you to the upstream package for this source.",
      "primaryActionLabel": "Download for OpenClaw",
      "primaryActionHref": "/downloads/product-manager-toolkit"
    },
    "validation": {
      "installChecklist": [
        "Use the Yavira download entry.",
        "Review SKILL.md after the package is downloaded.",
        "Confirm the extracted package contains the expected setup assets."
      ],
      "postInstallChecks": [
        "Confirm the extracted package includes the expected docs or setup files.",
        "Validate the skill or prompts are available in your target agent workspace.",
        "Capture any manual follow-up steps the agent could not complete."
      ]
    },
    "downloadPageUrl": "https://openagent3.xyz/downloads/product-manager-toolkit",
    "agentPageUrl": "https://openagent3.xyz/skills/product-manager-toolkit/agent",
    "manifestUrl": "https://openagent3.xyz/skills/product-manager-toolkit/agent.json",
    "briefUrl": "https://openagent3.xyz/skills/product-manager-toolkit/agent.md"
  },
  "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. Read SKILL.md from the extracted folder and install it by following the included instructions. 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. Summarize what changed and any follow-up checks I should run."
      }
    ]
  },
  "documentation": {
    "source": "clawhub",
    "primaryDoc": "SKILL.md",
    "sections": [
      {
        "title": "Product Manager Toolkit",
        "body": "Essential tools and frameworks for modern product management, from discovery to delivery."
      },
      {
        "title": "Table of Contents",
        "body": "Quick Start\nCore Workflows\n\nFeature Prioritization\nCustomer Discovery\nPRD Development\n\n\nTools Reference\n\nRICE Prioritizer\nCustomer Interview Analyzer\n\n\nInput/Output Examples\nIntegration Points\nCommon Pitfalls"
      },
      {
        "title": "For Feature Prioritization",
        "body": "# Create sample data file\npython scripts/rice_prioritizer.py sample\n\n# Run prioritization with team capacity\npython scripts/rice_prioritizer.py sample_features.csv --capacity 15"
      },
      {
        "title": "For Interview Analysis",
        "body": "python scripts/customer_interview_analyzer.py interview_transcript.txt"
      },
      {
        "title": "For PRD Creation",
        "body": "Choose template from references/prd_templates.md\nFill sections based on discovery work\nReview with engineering for feasibility\nVersion control in project management tool"
      },
      {
        "title": "Feature Prioritization Process",
        "body": "Gather → Score → Analyze → Plan → Validate → Execute\n\nStep 1: Gather Feature Requests\n\nCustomer feedback (support tickets, interviews)\nSales requests (CRM pipeline blockers)\nTechnical debt (engineering input)\nStrategic initiatives (leadership goals)\n\nStep 2: Score with RICE\n\n# Input: CSV with features\npython scripts/rice_prioritizer.py features.csv --capacity 20\n\nSee references/frameworks.md for RICE formula and scoring guidelines.\n\nStep 3: Analyze Portfolio\n\nReview the tool output for:\n\nQuick wins vs big bets distribution\nEffort concentration (avoid all XL projects)\nStrategic alignment gaps\n\nStep 4: Generate Roadmap\n\nQuarterly capacity allocation\nDependency identification\nStakeholder communication plan\n\nStep 5: Validate Results\n\nBefore finalizing the roadmap:\n\nCompare top priorities against strategic goals\n Run sensitivity analysis (what if estimates are wrong by 2x?)\n Review with key stakeholders for blind spots\n Check for missing dependencies between features\n Validate effort estimates with engineering\n\nStep 6: Execute and Iterate\n\nShare roadmap with team\nTrack actual vs estimated effort\nRevisit priorities quarterly\nUpdate RICE inputs based on learnings"
      },
      {
        "title": "Customer Discovery Process",
        "body": "Plan → Recruit → Interview → Analyze → Synthesize → Validate\n\nStep 1: Plan Research\n\nDefine research questions\nIdentify target segments\nCreate interview script (see references/frameworks.md)\n\nStep 2: Recruit Participants\n\n5-8 interviews per segment\nMix of power users and churned users\nIncentivize appropriately\n\nStep 3: Conduct Interviews\n\nUse semi-structured format\nFocus on problems, not solutions\nRecord with permission\nTake minimal notes during interview\n\nStep 4: Analyze Insights\n\npython scripts/customer_interview_analyzer.py transcript.txt\n\nExtracts:\n\nPain points with severity\nFeature requests with priority\nJobs to be done patterns\nSentiment and key themes\nNotable quotes\n\nStep 5: Synthesize Findings\n\nGroup similar pain points across interviews\nIdentify patterns (3+ mentions = pattern)\nMap to opportunity areas using Opportunity Solution Tree\nPrioritize opportunities by frequency and severity\n\nStep 6: Validate Solutions\n\nBefore building:\n\nCreate solution hypotheses (see references/frameworks.md)\n Test with low-fidelity prototypes\n Measure actual behavior vs stated preference\n Iterate based on feedback\n Document learnings for future research"
      },
      {
        "title": "PRD Development Process",
        "body": "Scope → Draft → Review → Refine → Approve → Track\n\nStep 1: Choose Template\n\nSelect from references/prd_templates.md:\n\nTemplateUse CaseTimelineStandard PRDComplex features, cross-team6-8 weeksOne-Page PRDSimple features, single team2-4 weeksFeature BriefExploration phase1 weekAgile EpicSprint-based deliveryOngoing\n\nStep 2: Draft Content\n\nLead with problem statement\nDefine success metrics upfront\nExplicitly state out-of-scope items\nInclude wireframes or mockups\n\nStep 3: Review Cycle\n\nEngineering: feasibility and effort\nDesign: user experience gaps\nSales: market validation\nSupport: operational impact\n\nStep 4: Refine Based on Feedback\n\nAddress technical constraints\nAdjust scope to fit timeline\nDocument trade-off decisions\n\nStep 5: Approval and Kickoff\n\nStakeholder sign-off\nSprint planning integration\nCommunication to broader team\n\nStep 6: Track Execution\n\nAfter launch:\n\nCompare actual metrics vs targets\n Conduct user feedback sessions\n Document what worked and what didn't\n Update estimation accuracy data\n Share learnings with team"
      },
      {
        "title": "RICE Prioritizer",
        "body": "Advanced RICE framework implementation with portfolio analysis.\n\nFeatures:\n\nRICE score calculation with configurable weights\nPortfolio balance analysis (quick wins vs big bets)\nQuarterly roadmap generation based on capacity\nMultiple output formats (text, JSON, CSV)\n\nCSV Input Format:\n\nname,reach,impact,confidence,effort,description\nUser Dashboard Redesign,5000,high,high,l,Complete redesign\nMobile Push Notifications,10000,massive,medium,m,Add push support\nDark Mode,8000,medium,high,s,Dark theme option\n\nCommands:\n\n# Create sample data\npython scripts/rice_prioritizer.py sample\n\n# Run with default capacity (10 person-months)\npython scripts/rice_prioritizer.py features.csv\n\n# Custom capacity\npython scripts/rice_prioritizer.py features.csv --capacity 20\n\n# JSON output for integration\npython scripts/rice_prioritizer.py features.csv --output json\n\n# CSV output for spreadsheets\npython scripts/rice_prioritizer.py features.csv --output csv"
      },
      {
        "title": "Customer Interview Analyzer",
        "body": "NLP-based interview analysis for extracting actionable insights.\n\nCapabilities:\n\nPain point extraction with severity assessment\nFeature request identification and classification\nJobs-to-be-done pattern recognition\nSentiment analysis per section\nTheme and quote extraction\nCompetitor mention detection\n\nCommands:\n\n# Analyze interview transcript\npython scripts/customer_interview_analyzer.py interview.txt\n\n# JSON output for aggregation\npython scripts/customer_interview_analyzer.py interview.txt json"
      },
      {
        "title": "Input/Output Examples",
        "body": "→ See references/input-output-examples.md for details"
      },
      {
        "title": "Integration Points",
        "body": "Compatible tools and platforms:\n\nCategoryPlatformsAnalyticsAmplitude, Mixpanel, Google AnalyticsRoadmappingProductBoard, Aha!, Roadmunk, ProductplanDesignFigma, Sketch, MiroDevelopmentJira, Linear, GitHub, AsanaResearchDovetail, UserVoice, Pendo, MazeCommunicationSlack, Notion, Confluence\n\nJSON export enables integration with most tools:\n\n# Export for Jira import\npython scripts/rice_prioritizer.py features.csv --output json > priorities.json\n\n# Export for dashboard\npython scripts/customer_interview_analyzer.py interview.txt json > insights.json"
      },
      {
        "title": "Common Pitfalls to Avoid",
        "body": "PitfallDescriptionPreventionSolution-FirstJumping to features before understanding problemsStart every PRD with problem statementAnalysis ParalysisOver-researching without shippingSet time-boxes for research phasesFeature FactoryShipping features without measuring impactDefine success metrics before buildingIgnoring Tech DebtNot allocating time for platform healthReserve 20% capacity for maintenanceStakeholder SurpriseNot communicating early and oftenWeekly async updates, monthly demosMetric TheaterOptimizing vanity metrics over real valueTie metrics to user value delivered"
      },
      {
        "title": "Best Practices",
        "body": "Writing Great PRDs:\n\nStart with the problem, not the solution\nInclude clear success metrics upfront\nExplicitly state what's out of scope\nUse visuals (wireframes, flows, diagrams)\nKeep technical details in appendix\nVersion control all changes\n\nEffective Prioritization:\n\nMix quick wins with strategic bets\nConsider opportunity cost of delays\nAccount for dependencies between features\nBuffer 20% for unexpected work\nRevisit priorities quarterly\nCommunicate decisions with context\n\nCustomer Discovery:\n\nAsk \"why\" five times to find root cause\nFocus on past behavior, not future intentions\nAvoid leading questions (\"Wouldn't you love...\")\nInterview in the user's natural environment\nWatch for emotional reactions (pain = opportunity)\nValidate qualitative with quantitative data"
      },
      {
        "title": "Quick Reference",
        "body": "# Prioritization\npython scripts/rice_prioritizer.py features.csv --capacity 15\n\n# Interview Analysis\npython scripts/customer_interview_analyzer.py interview.txt\n\n# Generate sample data\npython scripts/rice_prioritizer.py sample\n\n# JSON outputs\npython scripts/rice_prioritizer.py features.csv --output json\npython scripts/customer_interview_analyzer.py interview.txt json"
      },
      {
        "title": "Reference Documents",
        "body": "references/prd_templates.md - PRD templates for different contexts\nreferences/frameworks.md - Detailed framework documentation (RICE, MoSCoW, Kano, JTBD, etc.)"
      }
    ],
    "body": "Product Manager Toolkit\n\nEssential tools and frameworks for modern product management, from discovery to delivery.\n\nTable of Contents\nQuick Start\nCore Workflows\nFeature Prioritization\nCustomer Discovery\nPRD Development\nTools Reference\nRICE Prioritizer\nCustomer Interview Analyzer\nInput/Output Examples\nIntegration Points\nCommon Pitfalls\nQuick Start\nFor Feature Prioritization\n# Create sample data file\npython scripts/rice_prioritizer.py sample\n\n# Run prioritization with team capacity\npython scripts/rice_prioritizer.py sample_features.csv --capacity 15\n\nFor Interview Analysis\npython scripts/customer_interview_analyzer.py interview_transcript.txt\n\nFor PRD Creation\nChoose template from references/prd_templates.md\nFill sections based on discovery work\nReview with engineering for feasibility\nVersion control in project management tool\nCore Workflows\nFeature Prioritization Process\nGather → Score → Analyze → Plan → Validate → Execute\n\nStep 1: Gather Feature Requests\nCustomer feedback (support tickets, interviews)\nSales requests (CRM pipeline blockers)\nTechnical debt (engineering input)\nStrategic initiatives (leadership goals)\nStep 2: Score with RICE\n# Input: CSV with features\npython scripts/rice_prioritizer.py features.csv --capacity 20\n\n\nSee references/frameworks.md for RICE formula and scoring guidelines.\n\nStep 3: Analyze Portfolio\n\nReview the tool output for:\n\nQuick wins vs big bets distribution\nEffort concentration (avoid all XL projects)\nStrategic alignment gaps\nStep 4: Generate Roadmap\nQuarterly capacity allocation\nDependency identification\nStakeholder communication plan\nStep 5: Validate Results\n\nBefore finalizing the roadmap:\n\n Compare top priorities against strategic goals\n Run sensitivity analysis (what if estimates are wrong by 2x?)\n Review with key stakeholders for blind spots\n Check for missing dependencies between features\n Validate effort estimates with engineering\nStep 6: Execute and Iterate\nShare roadmap with team\nTrack actual vs estimated effort\nRevisit priorities quarterly\nUpdate RICE inputs based on learnings\nCustomer Discovery Process\nPlan → Recruit → Interview → Analyze → Synthesize → Validate\n\nStep 1: Plan Research\nDefine research questions\nIdentify target segments\nCreate interview script (see references/frameworks.md)\nStep 2: Recruit Participants\n5-8 interviews per segment\nMix of power users and churned users\nIncentivize appropriately\nStep 3: Conduct Interviews\nUse semi-structured format\nFocus on problems, not solutions\nRecord with permission\nTake minimal notes during interview\nStep 4: Analyze Insights\npython scripts/customer_interview_analyzer.py transcript.txt\n\n\nExtracts:\n\nPain points with severity\nFeature requests with priority\nJobs to be done patterns\nSentiment and key themes\nNotable quotes\nStep 5: Synthesize Findings\nGroup similar pain points across interviews\nIdentify patterns (3+ mentions = pattern)\nMap to opportunity areas using Opportunity Solution Tree\nPrioritize opportunities by frequency and severity\nStep 6: Validate Solutions\n\nBefore building:\n\n Create solution hypotheses (see references/frameworks.md)\n Test with low-fidelity prototypes\n Measure actual behavior vs stated preference\n Iterate based on feedback\n Document learnings for future research\nPRD Development Process\nScope → Draft → Review → Refine → Approve → Track\n\nStep 1: Choose Template\n\nSelect from references/prd_templates.md:\n\nTemplate\tUse Case\tTimeline\nStandard PRD\tComplex features, cross-team\t6-8 weeks\nOne-Page PRD\tSimple features, single team\t2-4 weeks\nFeature Brief\tExploration phase\t1 week\nAgile Epic\tSprint-based delivery\tOngoing\nStep 2: Draft Content\nLead with problem statement\nDefine success metrics upfront\nExplicitly state out-of-scope items\nInclude wireframes or mockups\nStep 3: Review Cycle\nEngineering: feasibility and effort\nDesign: user experience gaps\nSales: market validation\nSupport: operational impact\nStep 4: Refine Based on Feedback\nAddress technical constraints\nAdjust scope to fit timeline\nDocument trade-off decisions\nStep 5: Approval and Kickoff\nStakeholder sign-off\nSprint planning integration\nCommunication to broader team\nStep 6: Track Execution\n\nAfter launch:\n\n Compare actual metrics vs targets\n Conduct user feedback sessions\n Document what worked and what didn't\n Update estimation accuracy data\n Share learnings with team\nTools Reference\nRICE Prioritizer\n\nAdvanced RICE framework implementation with portfolio analysis.\n\nFeatures:\n\nRICE score calculation with configurable weights\nPortfolio balance analysis (quick wins vs big bets)\nQuarterly roadmap generation based on capacity\nMultiple output formats (text, JSON, CSV)\n\nCSV Input Format:\n\nname,reach,impact,confidence,effort,description\nUser Dashboard Redesign,5000,high,high,l,Complete redesign\nMobile Push Notifications,10000,massive,medium,m,Add push support\nDark Mode,8000,medium,high,s,Dark theme option\n\n\nCommands:\n\n# Create sample data\npython scripts/rice_prioritizer.py sample\n\n# Run with default capacity (10 person-months)\npython scripts/rice_prioritizer.py features.csv\n\n# Custom capacity\npython scripts/rice_prioritizer.py features.csv --capacity 20\n\n# JSON output for integration\npython scripts/rice_prioritizer.py features.csv --output json\n\n# CSV output for spreadsheets\npython scripts/rice_prioritizer.py features.csv --output csv\n\nCustomer Interview Analyzer\n\nNLP-based interview analysis for extracting actionable insights.\n\nCapabilities:\n\nPain point extraction with severity assessment\nFeature request identification and classification\nJobs-to-be-done pattern recognition\nSentiment analysis per section\nTheme and quote extraction\nCompetitor mention detection\n\nCommands:\n\n# Analyze interview transcript\npython scripts/customer_interview_analyzer.py interview.txt\n\n# JSON output for aggregation\npython scripts/customer_interview_analyzer.py interview.txt json\n\nInput/Output Examples\n\n→ See references/input-output-examples.md for details\n\nIntegration Points\n\nCompatible tools and platforms:\n\nCategory\tPlatforms\nAnalytics\tAmplitude, Mixpanel, Google Analytics\nRoadmapping\tProductBoard, Aha!, Roadmunk, Productplan\nDesign\tFigma, Sketch, Miro\nDevelopment\tJira, Linear, GitHub, Asana\nResearch\tDovetail, UserVoice, Pendo, Maze\nCommunication\tSlack, Notion, Confluence\n\nJSON export enables integration with most tools:\n\n# Export for Jira import\npython scripts/rice_prioritizer.py features.csv --output json > priorities.json\n\n# Export for dashboard\npython scripts/customer_interview_analyzer.py interview.txt json > insights.json\n\nCommon Pitfalls to Avoid\nPitfall\tDescription\tPrevention\nSolution-First\tJumping to features before understanding problems\tStart every PRD with problem statement\nAnalysis Paralysis\tOver-researching without shipping\tSet time-boxes for research phases\nFeature Factory\tShipping features without measuring impact\tDefine success metrics before building\nIgnoring Tech Debt\tNot allocating time for platform health\tReserve 20% capacity for maintenance\nStakeholder Surprise\tNot communicating early and often\tWeekly async updates, monthly demos\nMetric Theater\tOptimizing vanity metrics over real value\tTie metrics to user value delivered\nBest Practices\n\nWriting Great PRDs:\n\nStart with the problem, not the solution\nInclude clear success metrics upfront\nExplicitly state what's out of scope\nUse visuals (wireframes, flows, diagrams)\nKeep technical details in appendix\nVersion control all changes\n\nEffective Prioritization:\n\nMix quick wins with strategic bets\nConsider opportunity cost of delays\nAccount for dependencies between features\nBuffer 20% for unexpected work\nRevisit priorities quarterly\nCommunicate decisions with context\n\nCustomer Discovery:\n\nAsk \"why\" five times to find root cause\nFocus on past behavior, not future intentions\nAvoid leading questions (\"Wouldn't you love...\")\nInterview in the user's natural environment\nWatch for emotional reactions (pain = opportunity)\nValidate qualitative with quantitative data\nQuick Reference\n# Prioritization\npython scripts/rice_prioritizer.py features.csv --capacity 15\n\n# Interview Analysis\npython scripts/customer_interview_analyzer.py interview.txt\n\n# Generate sample data\npython scripts/rice_prioritizer.py sample\n\n# JSON outputs\npython scripts/rice_prioritizer.py features.csv --output json\npython scripts/customer_interview_analyzer.py interview.txt json\n\nReference Documents\nreferences/prd_templates.md - PRD templates for different contexts\nreferences/frameworks.md - Detailed framework documentation (RICE, MoSCoW, Kano, JTBD, etc.)"
  },
  "trust": {
    "sourceLabel": "tencent",
    "provenanceUrl": "https://clawhub.ai/alirezarezvani/product-manager-toolkit",
    "publisherUrl": "https://clawhub.ai/alirezarezvani/product-manager-toolkit",
    "owner": "alirezarezvani",
    "version": "2.1.1",
    "license": null,
    "verificationStatus": "Indexed source record"
  },
  "links": {
    "detailUrl": "https://openagent3.xyz/skills/product-manager-toolkit",
    "downloadUrl": "https://openagent3.xyz/downloads/product-manager-toolkit",
    "agentUrl": "https://openagent3.xyz/skills/product-manager-toolkit/agent",
    "manifestUrl": "https://openagent3.xyz/skills/product-manager-toolkit/agent.json",
    "briefUrl": "https://openagent3.xyz/skills/product-manager-toolkit/agent.md"
  }
}