{
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  "item": {
    "slug": "afrexai-agent-manager",
    "name": "AI Agent Manager Playbook",
    "source": "tencent",
    "type": "skill",
    "category": "AI 智能",
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          "body": "I downloaded a skill package from Yavira. 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."
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    "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. 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."
      }
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  "documentation": {
    "source": "clawhub",
    "primaryDoc": "SKILL.md",
    "sections": [
      {
        "title": "AI Agent Manager Playbook",
        "body": "Your company deployed AI agents. Now what? This skill turns you into the person who actually makes them productive — the Agent Manager."
      },
      {
        "title": "What This Does",
        "body": "Gives you a complete framework for managing autonomous AI agents across your organization. Role definition, performance metrics, escalation protocols, governance, and team structure."
      },
      {
        "title": "The Agent Manager Role",
        "body": "Based on Harvard Business Review's Feb 2026 research: companies deploying AI agents without dedicated management see 60%+ failure rates. The ones that assign Agent Managers see 3-4x better outcomes."
      },
      {
        "title": "Core Responsibilities",
        "body": "Agent Portfolio Management — Which agents run, which get retired, which get built next\nPerformance Monitoring — Task completion rates, accuracy, cost per action, escalation frequency\nEscalation Design — When agents hand off to humans, how, and what context they pass\nGovernance & Compliance — Ensuring agents operate within policy, legal, and ethical boundaries\nROI Tracking — Proving agent value in hours saved, revenue generated, errors prevented"
      },
      {
        "title": "Agent Performance Scorecard",
        "body": "Rate each agent monthly (1-5 scale):\n\nDimensionWhat to MeasureTargetReliabilityTask completion without errors>95%SpeedAvg time per task vs human baseline<30% of human timeCost EfficiencyCost per action vs manual equivalent<20% of manual costEscalation Rate% tasks requiring human intervention<10%User SatisfactionInternal user NPS for agent interactions>40 NPSCompliancePolicy violations or audit flags0"
      },
      {
        "title": "Phase 1: Discovery (Week 1-2)",
        "body": "Audit all manual processes across departments\nScore each by: volume × time × error rate × cost\nRank by automation ROI — top 5 become agent candidates\nDocument current process with decision trees"
      },
      {
        "title": "Phase 2: Build & Test (Week 3-6)",
        "body": "Define agent scope: inputs, outputs, decision boundaries\nBuild with guardrails: rate limits, approval gates, kill switches\nShadow mode: agent runs alongside human, outputs compared\nAcceptance criteria: 95% accuracy over 100+ test cases"
      },
      {
        "title": "Phase 3: Deploy & Monitor (Week 7-8)",
        "body": "Gradual rollout: 10% → 25% → 50% → 100% of volume\nDaily monitoring dashboard (first 2 weeks)\nWeekly reviews (ongoing)\nEscalation paths documented and tested"
      },
      {
        "title": "Phase 4: Optimize (Ongoing)",
        "body": "Monthly performance reviews against scorecard\nQuarterly ROI assessment\nAgent retirement criteria: <80% reliability for 2 consecutive months\nExpansion criteria: >95% reliability + positive ROI for 3 months"
      },
      {
        "title": "Escalation Protocol Design",
        "body": "Level 1: Agent handles autonomously (target: 90%+ of volume)\nLevel 2: Agent flags for human review before executing (5-8%)\nLevel 3: Agent stops and routes to human immediately (1-3%)\nLevel 4: Agent shuts down, alerts on-call manager (<1%)"
      },
      {
        "title": "Escalation Triggers",
        "body": "Confidence score below threshold\nFinancial amount exceeds limit ($X)\nCustomer sentiment detected as negative\nRegulatory/compliance topic detected\nNovel situation not in training data\nContradictory instructions received"
      },
      {
        "title": "Small Company (1-50 employees)",
        "body": "1 Agent Manager (often the CTO or ops lead)\nManaging 3-8 agents\nTime commitment: 5-10 hours/week"
      },
      {
        "title": "Mid-Market (50-500 employees)",
        "body": "1 dedicated Agent Manager\n1 Agent Engineer (builds/maintains)\nManaging 10-30 agents\nBudget: $120K-$180K/year fully loaded"
      },
      {
        "title": "Enterprise (500+ employees)",
        "body": "Agent Management Team (3-5 people)\nHead of AI Operations\nAgent Engineers (2-3)\nAgent Compliance Officer\nManaging 50-200+ agents\nBudget: $500K-$1.2M/year"
      },
      {
        "title": "Agent Registry",
        "body": "Every agent must have:\n\nUnique ID and name\nOwner (human accountable)\nScope document (what it can/cannot do)\nData access permissions\nEscalation protocol\nLast audit date\nPerformance scorecard link"
      },
      {
        "title": "Monthly Agent Review",
        "body": "Pull performance data for all agents\nFlag any below threshold\nReview escalation logs for patterns\nUpdate scope documents if needed\nRetire underperformers\nPropose new agent candidates"
      },
      {
        "title": "Quarterly Board Report",
        "body": "Total agents active\nHours saved this quarter\nCost savings vs manual\nIncidents/compliance flags\nROI per agent category\nNext quarter agent roadmap"
      },
      {
        "title": "Common Mistakes",
        "body": "No kill switch — Every agent needs an off button. No exceptions.\nSet and forget — Agents drift. Monthly reviews are minimum.\nToo much autonomy too fast — Start with shadow mode. Always.\nNo escalation path — If the agent can't hand off to a human, it will fail silently.\nMeasuring activity not outcomes — \"Agent processed 10,000 tasks\" means nothing if 40% were wrong.\nOne person owns all agents — Bus factor of 1 = organizational risk."
      },
      {
        "title": "ROI Calculator",
        "body": "Monthly Agent Cost = (API costs + infrastructure + management time)\nMonthly Human Cost = (hours saved × avg hourly rate)\nMonthly ROI = (Human Cost - Agent Cost) / Agent Cost × 100\n\nExample (Customer Support Agent):\n- API + infra: $800/month\n- Management overhead: $400/month (5 hrs × $80/hr)\n- Hours saved: 160/month (1 FTE equivalent)\n- Human cost: $8,000/month ($50/hr fully loaded)\n- Monthly ROI: ($8,000 - $1,200) / $1,200 = 567%\n- Payback period: <1 month"
      },
      {
        "title": "Industry Applications",
        "body": "IndustryTop Agent Use CasesAvg ROISaaSCustomer onboarding, ticket triage, usage analytics400-600%Financial ServicesKYC checks, transaction monitoring, report generation300-500%HealthcareAppointment scheduling, prior auth, patient follow-up250-400%LegalDocument review, contract extraction, research500-800%EcommerceOrder tracking, returns processing, inventory alerts350-550%Professional ServicesTime entry, invoice generation, proposal drafts300-450%ManufacturingQuality inspection reports, maintenance scheduling200-400%ConstructionPermit tracking, safety compliance, RFI management250-350%Real EstateLead qualification, showing scheduling, market reports300-500%RecruitmentResume screening, interview scheduling, reference checks400-700%"
      },
      {
        "title": "Get the Full Industry Context",
        "body": "Each industry above maps to a specialized context pack with 50+ pages of workflows, benchmarks, and implementation guides:\n\nAfrexAI Context Packs — $47 each or bundle and save:\n\n🛒 Browse All 10 Packs\n🧮 AI Revenue Calculator — See exactly what automation saves your company\n🧙 Agent Setup Wizard — Get a custom agent config in 5 minutes\n\nBundles: Pick 3 for $97 | All 10 for $197 | Everything Bundle $247"
      }
    ],
    "body": "AI Agent Manager Playbook\n\nYour company deployed AI agents. Now what? This skill turns you into the person who actually makes them productive — the Agent Manager.\n\nWhat This Does\n\nGives you a complete framework for managing autonomous AI agents across your organization. Role definition, performance metrics, escalation protocols, governance, and team structure.\n\nThe Agent Manager Role\n\nBased on Harvard Business Review's Feb 2026 research: companies deploying AI agents without dedicated management see 60%+ failure rates. The ones that assign Agent Managers see 3-4x better outcomes.\n\nCore Responsibilities\nAgent Portfolio Management — Which agents run, which get retired, which get built next\nPerformance Monitoring — Task completion rates, accuracy, cost per action, escalation frequency\nEscalation Design — When agents hand off to humans, how, and what context they pass\nGovernance & Compliance — Ensuring agents operate within policy, legal, and ethical boundaries\nROI Tracking — Proving agent value in hours saved, revenue generated, errors prevented\nAgent Performance Scorecard\n\nRate each agent monthly (1-5 scale):\n\nDimension\tWhat to Measure\tTarget\nReliability\tTask completion without errors\t>95%\nSpeed\tAvg time per task vs human baseline\t<30% of human time\nCost Efficiency\tCost per action vs manual equivalent\t<20% of manual cost\nEscalation Rate\t% tasks requiring human intervention\t<10%\nUser Satisfaction\tInternal user NPS for agent interactions\t>40 NPS\nCompliance\tPolicy violations or audit flags\t0\nAgent Lifecycle Framework\nPhase 1: Discovery (Week 1-2)\nAudit all manual processes across departments\nScore each by: volume × time × error rate × cost\nRank by automation ROI — top 5 become agent candidates\nDocument current process with decision trees\nPhase 2: Build & Test (Week 3-6)\nDefine agent scope: inputs, outputs, decision boundaries\nBuild with guardrails: rate limits, approval gates, kill switches\nShadow mode: agent runs alongside human, outputs compared\nAcceptance criteria: 95% accuracy over 100+ test cases\nPhase 3: Deploy & Monitor (Week 7-8)\nGradual rollout: 10% → 25% → 50% → 100% of volume\nDaily monitoring dashboard (first 2 weeks)\nWeekly reviews (ongoing)\nEscalation paths documented and tested\nPhase 4: Optimize (Ongoing)\nMonthly performance reviews against scorecard\nQuarterly ROI assessment\nAgent retirement criteria: <80% reliability for 2 consecutive months\nExpansion criteria: >95% reliability + positive ROI for 3 months\nEscalation Protocol Design\nLevel 1: Agent handles autonomously (target: 90%+ of volume)\nLevel 2: Agent flags for human review before executing (5-8%)\nLevel 3: Agent stops and routes to human immediately (1-3%)\nLevel 4: Agent shuts down, alerts on-call manager (<1%)\n\nEscalation Triggers\nConfidence score below threshold\nFinancial amount exceeds limit ($X)\nCustomer sentiment detected as negative\nRegulatory/compliance topic detected\nNovel situation not in training data\nContradictory instructions received\nTeam Structure\nSmall Company (1-50 employees)\n1 Agent Manager (often the CTO or ops lead)\nManaging 3-8 agents\nTime commitment: 5-10 hours/week\nMid-Market (50-500 employees)\n1 dedicated Agent Manager\n1 Agent Engineer (builds/maintains)\nManaging 10-30 agents\nBudget: $120K-$180K/year fully loaded\nEnterprise (500+ employees)\nAgent Management Team (3-5 people)\nHead of AI Operations\nAgent Engineers (2-3)\nAgent Compliance Officer\nManaging 50-200+ agents\nBudget: $500K-$1.2M/year\nGovernance Framework\nAgent Registry\n\nEvery agent must have:\n\nUnique ID and name\nOwner (human accountable)\nScope document (what it can/cannot do)\nData access permissions\nEscalation protocol\nLast audit date\nPerformance scorecard link\nMonthly Agent Review\nPull performance data for all agents\nFlag any below threshold\nReview escalation logs for patterns\nUpdate scope documents if needed\nRetire underperformers\nPropose new agent candidates\nQuarterly Board Report\nTotal agents active\nHours saved this quarter\nCost savings vs manual\nIncidents/compliance flags\nROI per agent category\nNext quarter agent roadmap\nCommon Mistakes\nNo kill switch — Every agent needs an off button. No exceptions.\nSet and forget — Agents drift. Monthly reviews are minimum.\nToo much autonomy too fast — Start with shadow mode. Always.\nNo escalation path — If the agent can't hand off to a human, it will fail silently.\nMeasuring activity not outcomes — \"Agent processed 10,000 tasks\" means nothing if 40% were wrong.\nOne person owns all agents — Bus factor of 1 = organizational risk.\nROI Calculator\nMonthly Agent Cost = (API costs + infrastructure + management time)\nMonthly Human Cost = (hours saved × avg hourly rate)\nMonthly ROI = (Human Cost - Agent Cost) / Agent Cost × 100\n\nExample (Customer Support Agent):\n- API + infra: $800/month\n- Management overhead: $400/month (5 hrs × $80/hr)\n- Hours saved: 160/month (1 FTE equivalent)\n- Human cost: $8,000/month ($50/hr fully loaded)\n- Monthly ROI: ($8,000 - $1,200) / $1,200 = 567%\n- Payback period: <1 month\n\nIndustry Applications\nIndustry\tTop Agent Use Cases\tAvg ROI\nSaaS\tCustomer onboarding, ticket triage, usage analytics\t400-600%\nFinancial Services\tKYC checks, transaction monitoring, report generation\t300-500%\nHealthcare\tAppointment scheduling, prior auth, patient follow-up\t250-400%\nLegal\tDocument review, contract extraction, research\t500-800%\nEcommerce\tOrder tracking, returns processing, inventory alerts\t350-550%\nProfessional Services\tTime entry, invoice generation, proposal drafts\t300-450%\nManufacturing\tQuality inspection reports, maintenance scheduling\t200-400%\nConstruction\tPermit tracking, safety compliance, RFI management\t250-350%\nReal Estate\tLead qualification, showing scheduling, market reports\t300-500%\nRecruitment\tResume screening, interview scheduling, reference checks\t400-700%\nGet the Full Industry Context\n\nEach industry above maps to a specialized context pack with 50+ pages of workflows, benchmarks, and implementation guides:\n\nAfrexAI Context Packs — $47 each or bundle and save:\n\n🛒 Browse All 10 Packs\n🧮 AI Revenue Calculator — See exactly what automation saves your company\n🧙 Agent Setup Wizard — Get a custom agent config in 5 minutes\n\nBundles: Pick 3 for $97 | All 10 for $197 | Everything Bundle $247"
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    "owner": "1kalin",
    "version": "1.0.0",
    "license": null,
    "verificationStatus": "Indexed source record"
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