{ "schemaVersion": "1.0", "item": { "slug": "afrexai-cloud-cost-audit", "name": "Cloud Cost Audit", "source": "tencent", "type": "skill", "category": "数据分析", "sourceUrl": "https://clawhub.ai/1kalin/afrexai-cloud-cost-audit", "canonicalUrl": "https://clawhub.ai/1kalin/afrexai-cloud-cost-audit", "targetPlatform": "OpenClaw" }, "install": { "downloadMode": "redirect", "downloadUrl": "/downloads/afrexai-cloud-cost-audit", "sourceDownloadUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=afrexai-cloud-cost-audit", "sourcePlatform": "tencent", "targetPlatform": "OpenClaw", "installMethod": "Manual import", "extraction": "Extract archive", "prerequisites": [ "OpenClaw" ], "packageFormat": "ZIP package", "includedAssets": [ "README.md", "SKILL.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. 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." } ] }, "sourceHealth": { "source": "tencent", "status": "healthy", "reason": "direct_download_ok", "recommendedAction": "download", "checkedAt": "2026-04-23T16:43:11.935Z", "expiresAt": "2026-04-30T16:43:11.935Z", "httpStatus": 200, "finalUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=4claw-imageboard", "contentType": "application/zip", "probeMethod": "head", "details": { "probeUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=4claw-imageboard", "contentDisposition": "attachment; filename=\"4claw-imageboard-1.0.1.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/afrexai-cloud-cost-audit" }, "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/afrexai-cloud-cost-audit", "agentPageUrl": "https://openagent3.xyz/skills/afrexai-cloud-cost-audit/agent", "manifestUrl": "https://openagent3.xyz/skills/afrexai-cloud-cost-audit/agent.json", "briefUrl": "https://openagent3.xyz/skills/afrexai-cloud-cost-audit/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. 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": "Cloud Cost Optimization Audit", "body": "Analyze cloud infrastructure spend across AWS, Azure, and GCP. Identify waste, rightsizing opportunities, and reserved instance savings." }, { "title": "What This Skill Does", "body": "When given cloud spend data (billing exports, cost explorer screenshots, or manual input), this skill:\n\nCategorizes spend across 8 cost domains (compute, storage, networking, databases, AI/ML, observability, security, licensing)\nIdentifies waste patterns using 12 common anti-patterns\nCalculates savings with specific dollar amounts per optimization\nPrioritizes actions by effort vs. impact (quick wins → strategic moves)\nGenerates executive summary with 90-day roadmap" }, { "title": "1. Compute (typically 40-55% of total)", "body": "Idle instances: >30% idle = waste. Benchmark: <10% idle capacity\nRightsizing: 60% of instances are oversized by 1+ size category\nSpot/preemptible: Batch workloads not on spot = 60-80% overpay\nReserved/savings plans: On-demand for steady-state = 30-50% overpay\nContainer density: <40% CPU utilization on nodes = poor bin-packing" }, { "title": "2. Storage (typically 10-20%)", "body": "Tiering: Data not accessed in 90 days still on hot storage = 60-80% overpay\nSnapshot sprawl: Orphaned snapshots older than 30 days\nDuplicate data: Cross-region replication without business justification\nObject lifecycle: No lifecycle policies = guaranteed bloat" }, { "title": "3. Networking (typically 8-15%)", "body": "Cross-AZ traffic: Unnecessary data transfer between zones ($0.01-0.02/GB)\nNAT gateway abuse: High-throughput through NAT vs. VPC endpoints\nCDN miss rate: >20% miss rate = CDN config issue\nEgress optimization: No committed use discounts on egress" }, { "title": "4. Databases (typically 10-20%)", "body": "Over-provisioned RDS/Cloud SQL: Multi-AZ for dev/staging environments\nRead replica sprawl: Replicas with <5% query load\nDynamoDB/Cosmos over-provisioning: Provisioned capacity 3x+ actual usage\nLicense waste: Commercial DB when open-source works" }, { "title": "5. AI/ML Infrastructure (growing — 5-25%)", "body": "GPU idle time: Training instances running 24/7 for 4hr/day workloads\nInference over-provisioning: GPU instances for CPU-viable inference\nModel storage: Old model versions consuming storage\nAPI costs: Frontier model API calls without caching layer" }, { "title": "6. Observability (typically 3-8%)", "body": "Log ingestion bloat: Debug logs in production, duplicate log streams\nMetric cardinality: High-cardinality custom metrics ($$$)\nTrace sampling: 100% trace sampling when 10% suffices\nRetention overkill: 13-month retention for non-compliance data" }, { "title": "7. Security (typically 2-5%)", "body": "WAF rule bloat: Managed rule groups not actively tuned\nKey management: KMS keys for non-sensitive data\nCompliance scanning: Overlapping tools doing same checks" }, { "title": "8. Licensing (typically 5-15%)", "body": "Shelfware: Paid seats not logged in 60+ days\nDuplicate tools: Multiple tools solving same problem\nEnterprise tiers: Enterprise features unused, paying enterprise price" }, { "title": "12 Waste Anti-Patterns", "body": "#PatternTypical WasteFix Effort1Zombie resources (stopped but attached)5-15% of billLow2Over-provisioned instances15-30% computeMedium3No reserved capacity strategy25-40% computeMedium4Hot storage hoarding40-70% storageLow5Cross-AZ data transfer abuse10-30% networkMedium6Dev/staging mirrors production20-40% of envsLow7Orphaned snapshots/AMIs3-8% storageLow8Log ingestion without sampling30-60% observabilityLow9GPU instances for CPU workloads70-85% computeMedium10No spot/preemptible for batch60-80% batchMedium11Shelfware licenses20-40% licensingLow12No tagging = no accountabilityUnmeasurableHigh" }, { "title": "Savings Estimation Framework", "body": "For each finding, calculate:\n\nAnnual Savings = (Current Cost - Optimized Cost) × 12\nImplementation Cost = Engineering Hours × Loaded Rate\nROI = (Annual Savings - Implementation Cost) / Implementation Cost\nPayback Period = Implementation Cost / (Annual Savings / 12)" }, { "title": "Typical Savings by Company Size", "body": "Company SizeMonthly Cloud SpendTypical Waste %Annual SavingsStartup (5-15)$2K-$15K35-50%$8K-$90KGrowth (15-50)$15K-$80K25-40%$45K-$384KMid-market (50-200)$80K-$500K20-35%$192K-$2.1MEnterprise (200+)$500K-$5M+15-25%$900K-$15M+" }, { "title": "Output Format", "body": "Generate a report with:\n\nExecutive Summary: Total spend, waste identified, savings potential, top 3 quick wins\nDomain Breakdown: Spend per domain vs. benchmarks\nFindings Table: Each finding with current cost, optimized cost, savings, effort, priority\n90-Day Roadmap: Week 1-2 quick wins, Week 3-6 medium effort, Week 7-12 strategic\nGovernance Recommendations: Tagging strategy, budget alerts, review cadence" }, { "title": "Usage", "body": "Provide your cloud billing data in any format:\n\nAWS Cost Explorer export / Azure Cost Management / GCP Billing\nMonthly bill summary\nArchitecture description with approximate sizing\nOr just describe your stack and team size for estimates\n\nThe agent will analyze and produce the full optimization report." }, { "title": "Want Industry-Specific Cloud Optimization?", "body": "Different industries have different compliance, data residency, and workload patterns that change the optimization calculus entirely.\n\nGet your industry context pack — pre-built frameworks for Fintech, Healthcare, Legal, SaaS, Ecommerce, Construction, Real Estate, Recruitment, Manufacturing, and Professional Services.\n\n🛒 Browse packs: https://afrexai-cto.github.io/context-packs/\n🧮 Calculate your AI savings: https://afrexai-cto.github.io/ai-revenue-calculator/\n🤖 Set up your agent: https://afrexai-cto.github.io/agent-setup/\n\nBundle deals:\n\nPick 3 packs: $97\nAll 10 packs: $197\nEverything bundle: $247" } ], "body": "Cloud Cost Optimization Audit\n\nAnalyze cloud infrastructure spend across AWS, Azure, and GCP. Identify waste, rightsizing opportunities, and reserved instance savings.\n\nWhat This Skill Does\n\nWhen given cloud spend data (billing exports, cost explorer screenshots, or manual input), this skill:\n\nCategorizes spend across 8 cost domains (compute, storage, networking, databases, AI/ML, observability, security, licensing)\nIdentifies waste patterns using 12 common anti-patterns\nCalculates savings with specific dollar amounts per optimization\nPrioritizes actions by effort vs. impact (quick wins → strategic moves)\nGenerates executive summary with 90-day roadmap\nCost Domains & Benchmarks (2026)\n1. Compute (typically 40-55% of total)\nIdle instances: >30% idle = waste. Benchmark: <10% idle capacity\nRightsizing: 60% of instances are oversized by 1+ size category\nSpot/preemptible: Batch workloads not on spot = 60-80% overpay\nReserved/savings plans: On-demand for steady-state = 30-50% overpay\nContainer density: <40% CPU utilization on nodes = poor bin-packing\n2. Storage (typically 10-20%)\nTiering: Data not accessed in 90 days still on hot storage = 60-80% overpay\nSnapshot sprawl: Orphaned snapshots older than 30 days\nDuplicate data: Cross-region replication without business justification\nObject lifecycle: No lifecycle policies = guaranteed bloat\n3. Networking (typically 8-15%)\nCross-AZ traffic: Unnecessary data transfer between zones ($0.01-0.02/GB)\nNAT gateway abuse: High-throughput through NAT vs. VPC endpoints\nCDN miss rate: >20% miss rate = CDN config issue\nEgress optimization: No committed use discounts on egress\n4. Databases (typically 10-20%)\nOver-provisioned RDS/Cloud SQL: Multi-AZ for dev/staging environments\nRead replica sprawl: Replicas with <5% query load\nDynamoDB/Cosmos over-provisioning: Provisioned capacity 3x+ actual usage\nLicense waste: Commercial DB when open-source works\n5. AI/ML Infrastructure (growing — 5-25%)\nGPU idle time: Training instances running 24/7 for 4hr/day workloads\nInference over-provisioning: GPU instances for CPU-viable inference\nModel storage: Old model versions consuming storage\nAPI costs: Frontier model API calls without caching layer\n6. Observability (typically 3-8%)\nLog ingestion bloat: Debug logs in production, duplicate log streams\nMetric cardinality: High-cardinality custom metrics ($$$)\nTrace sampling: 100% trace sampling when 10% suffices\nRetention overkill: 13-month retention for non-compliance data\n7. Security (typically 2-5%)\nWAF rule bloat: Managed rule groups not actively tuned\nKey management: KMS keys for non-sensitive data\nCompliance scanning: Overlapping tools doing same checks\n8. Licensing (typically 5-15%)\nShelfware: Paid seats not logged in 60+ days\nDuplicate tools: Multiple tools solving same problem\nEnterprise tiers: Enterprise features unused, paying enterprise price\n12 Waste Anti-Patterns\n#\tPattern\tTypical Waste\tFix Effort\n1\tZombie resources (stopped but attached)\t5-15% of bill\tLow\n2\tOver-provisioned instances\t15-30% compute\tMedium\n3\tNo reserved capacity strategy\t25-40% compute\tMedium\n4\tHot storage hoarding\t40-70% storage\tLow\n5\tCross-AZ data transfer abuse\t10-30% network\tMedium\n6\tDev/staging mirrors production\t20-40% of envs\tLow\n7\tOrphaned snapshots/AMIs\t3-8% storage\tLow\n8\tLog ingestion without sampling\t30-60% observability\tLow\n9\tGPU instances for CPU workloads\t70-85% compute\tMedium\n10\tNo spot/preemptible for batch\t60-80% batch\tMedium\n11\tShelfware licenses\t20-40% licensing\tLow\n12\tNo tagging = no accountability\tUnmeasurable\tHigh\nSavings Estimation Framework\n\nFor each finding, calculate:\n\nAnnual Savings = (Current Cost - Optimized Cost) × 12\nImplementation Cost = Engineering Hours × Loaded Rate\nROI = (Annual Savings - Implementation Cost) / Implementation Cost\nPayback Period = Implementation Cost / (Annual Savings / 12)\n\nTypical Savings by Company Size\nCompany Size\tMonthly Cloud Spend\tTypical Waste %\tAnnual Savings\nStartup (5-15)\t$2K-$15K\t35-50%\t$8K-$90K\nGrowth (15-50)\t$15K-$80K\t25-40%\t$45K-$384K\nMid-market (50-200)\t$80K-$500K\t20-35%\t$192K-$2.1M\nEnterprise (200+)\t$500K-$5M+\t15-25%\t$900K-$15M+\nOutput Format\n\nGenerate a report with:\n\nExecutive Summary: Total spend, waste identified, savings potential, top 3 quick wins\nDomain Breakdown: Spend per domain vs. benchmarks\nFindings Table: Each finding with current cost, optimized cost, savings, effort, priority\n90-Day Roadmap: Week 1-2 quick wins, Week 3-6 medium effort, Week 7-12 strategic\nGovernance Recommendations: Tagging strategy, budget alerts, review cadence\nUsage\n\nProvide your cloud billing data in any format:\n\nAWS Cost Explorer export / Azure Cost Management / GCP Billing\nMonthly bill summary\nArchitecture description with approximate sizing\nOr just describe your stack and team size for estimates\n\nThe agent will analyze and produce the full optimization report.\n\nWant Industry-Specific Cloud Optimization?\n\nDifferent industries have different compliance, data residency, and workload patterns that change the optimization calculus entirely.\n\nGet your industry context pack — pre-built frameworks for Fintech, Healthcare, Legal, SaaS, Ecommerce, Construction, Real Estate, Recruitment, Manufacturing, and Professional Services.\n\n🛒 Browse packs: https://afrexai-cto.github.io/context-packs/ 🧮 Calculate your AI savings: https://afrexai-cto.github.io/ai-revenue-calculator/ 🤖 Set up your agent: https://afrexai-cto.github.io/agent-setup/\n\nBundle deals:\n\nPick 3 packs: $97\nAll 10 packs: $197\nEverything bundle: $247" }, "trust": { "sourceLabel": "tencent", "provenanceUrl": "https://clawhub.ai/1kalin/afrexai-cloud-cost-audit", "publisherUrl": "https://clawhub.ai/1kalin/afrexai-cloud-cost-audit", "owner": "1kalin", "version": "1.0.0", "license": null, "verificationStatus": "Indexed source record" }, "links": { "detailUrl": "https://openagent3.xyz/skills/afrexai-cloud-cost-audit", "downloadUrl": "https://openagent3.xyz/downloads/afrexai-cloud-cost-audit", "agentUrl": "https://openagent3.xyz/skills/afrexai-cloud-cost-audit/agent", "manifestUrl": "https://openagent3.xyz/skills/afrexai-cloud-cost-audit/agent.json", "briefUrl": "https://openagent3.xyz/skills/afrexai-cloud-cost-audit/agent.md" } }