{ "schemaVersion": "1.0", "item": { "slug": "mlops", "name": "MLOps", "source": "tencent", "type": "skill", "category": "AI 智能", "sourceUrl": "https://clawhub.ai/ivangdavila/mlops", "canonicalUrl": "https://clawhub.ai/ivangdavila/mlops", "targetPlatform": "OpenClaw" }, "install": { "downloadMode": "redirect", "downloadUrl": "/downloads/mlops", "sourceDownloadUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=mlops", "sourcePlatform": "tencent", "targetPlatform": "OpenClaw", "installMethod": "Manual import", "extraction": "Extract archive", "prerequisites": [ "OpenClaw" ], "packageFormat": "ZIP package", "includedAssets": [ "SKILL.md", "gpu.md", "monitoring.md", "pipelines.md", "reproducibility.md", "serving.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. 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", "slug": "mlops", "status": "healthy", "reason": "direct_download_ok", "recommendedAction": "download", "checkedAt": "2026-05-02T07:19:46.801Z", "expiresAt": "2026-05-09T07:19:46.801Z", "httpStatus": 200, "finalUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=mlops", "contentType": "application/zip", "probeMethod": "head", "details": { "probeUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=mlops", "contentDisposition": "attachment; filename=\"mlops-1.0.0.zip\"", "redirectLocation": null, "bodySnippet": null, "slug": "mlops" }, "scope": "item", "summary": "Item download looks usable.", "detail": "Yavira can redirect you to the upstream package for this item.", "primaryActionLabel": "Download for OpenClaw", "primaryActionHref": "/downloads/mlops" }, "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/mlops", "agentPageUrl": "https://openagent3.xyz/skills/mlops/agent", "manifestUrl": "https://openagent3.xyz/skills/mlops/agent.json", "briefUrl": "https://openagent3.xyz/skills/mlops/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": "Quick Reference", "body": "TopicFileKey TrapCI/CD and DAGspipelines.mdCoupling training/inference depsModel servingserving.mdCold start with large modelsDrift and alertsmonitoring.mdOnly technical metricsVersioningreproducibility.mdNot versioning preprocessingGPU infrastructuregpu.mdGPU request = full device" }, { "title": "Critical Traps", "body": "Training-Serving Skew:\n\nPreprocessing in notebook ≠ preprocessing in service → silent bugs\nPandas in notebook → memory leaks in production (use native types)\nFeature store values at training time ≠ serving time without proper joins\n\nGPU Memory:\n\nrequests.nvidia.com/gpu: 1 reserves ENTIRE GPU, not partial memory\nMIG/MPS sharing has real limitations (not plug-and-play)\nOOM on GPU kills pod with no useful logs\n\nModel Versioning ≠ Code Versioning:\n\nModel artifacts need separate versioning (MLflow, W&B, DVC)\nTraining data version + preprocessing version + code version = reproducibility\nRollback requires keeping old model versions deployable\n\nDrift Detection Timing:\n\nRetraining trigger isn't just \"drift > threshold\" → cost/benefit matters\nDelayed ground truth makes concept drift detection lag weeks\nUpstream data pipeline changes cause drift without model issues" }, { "title": "Scope", "body": "This skill ONLY covers:\n\nCI/CD pipelines for models\nModel serving and scaling\nMonitoring and drift detection\nReproducibility practices\nGPU infrastructure patterns\n\nDoes NOT cover: ML algorithms, feature engineering, hyperparameter tuning." } ], "body": "Quick Reference\nTopic\tFile\tKey Trap\nCI/CD and DAGs\tpipelines.md\tCoupling training/inference deps\nModel serving\tserving.md\tCold start with large models\nDrift and alerts\tmonitoring.md\tOnly technical metrics\nVersioning\treproducibility.md\tNot versioning preprocessing\nGPU infrastructure\tgpu.md\tGPU request = full device\nCritical Traps\n\nTraining-Serving Skew:\n\nPreprocessing in notebook ≠ preprocessing in service → silent bugs\nPandas in notebook → memory leaks in production (use native types)\nFeature store values at training time ≠ serving time without proper joins\n\nGPU Memory:\n\nrequests.nvidia.com/gpu: 1 reserves ENTIRE GPU, not partial memory\nMIG/MPS sharing has real limitations (not plug-and-play)\nOOM on GPU kills pod with no useful logs\n\nModel Versioning ≠ Code Versioning:\n\nModel artifacts need separate versioning (MLflow, W&B, DVC)\nTraining data version + preprocessing version + code version = reproducibility\nRollback requires keeping old model versions deployable\n\nDrift Detection Timing:\n\nRetraining trigger isn't just \"drift > threshold\" → cost/benefit matters\nDelayed ground truth makes concept drift detection lag weeks\nUpstream data pipeline changes cause drift without model issues\nScope\n\nThis skill ONLY covers:\n\nCI/CD pipelines for models\nModel serving and scaling\nMonitoring and drift detection\nReproducibility practices\nGPU infrastructure patterns\n\nDoes NOT cover: ML algorithms, feature engineering, hyperparameter tuning." }, "trust": { "sourceLabel": "tencent", "provenanceUrl": "https://clawhub.ai/ivangdavila/mlops", "publisherUrl": "https://clawhub.ai/ivangdavila/mlops", "owner": "ivangdavila", "version": "1.0.0", "license": null, "verificationStatus": "Indexed source record" }, "links": { "detailUrl": "https://openagent3.xyz/skills/mlops", "downloadUrl": "https://openagent3.xyz/downloads/mlops", "agentUrl": "https://openagent3.xyz/skills/mlops/agent", "manifestUrl": "https://openagent3.xyz/skills/mlops/agent.json", "briefUrl": "https://openagent3.xyz/skills/mlops/agent.md" } }