{
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    "slug": "dynamic-model-selector",
    "name": "Dynamic Model Selector",
    "source": "tencent",
    "type": "skill",
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      "Extract the archive and review SKILL.md first.",
      "Import or place the package into your OpenClaw setup."
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        },
        {
          "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."
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        "bodySnippet": null
      },
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      "detail": "Yavira can redirect you to the upstream package for this source.",
      "primaryActionLabel": "Download for OpenClaw",
      "primaryActionHref": "/downloads/dynamic-model-selector"
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        "Confirm the extracted package includes the expected docs or setup files.",
        "Validate the skill or prompts are available in your target agent workspace.",
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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. 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."
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  "documentation": {
    "source": "clawhub",
    "primaryDoc": "SKILL.md",
    "sections": [
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        "title": "Overview",
        "body": "This skill analyzes user queries to recommend the optimal AI model from available GitHub Copilot options, balancing performance, cost, and task requirements."
      },
      {
        "title": "How to Use",
        "body": "Provide the user query or task description.\nRun the classification script to analyze complexity.\nChoose the suggested model or adjust based on preferences."
      },
      {
        "title": "Classification Criteria",
        "body": "Simple tasks (short responses, basic chat): Use faster, free models like grok-code-fast-1.\nComplex reasoning (analysis, multi-step): Use advanced models like gpt-4o or claude-3.5-sonnet.\nCode generation: Prefer code-optimized models.\nCost sensitivity: Favor free models when possible."
      },
      {
        "title": "Example Usage",
        "body": "For a query like \"Explain quantum computing\": Classify as medium complexity -> Recommend gpt-4o.\n\nFor \"Write a Python function to sort a list\": Classify as code task -> Recommend grok-code-fast-1."
      },
      {
        "title": "scripts/",
        "body": "classify_task.py: Analyzes the query and outputs model recommendation."
      },
      {
        "title": "references/",
        "body": "models.md: Detailed list of available models, pros/cons, costs."
      }
    ],
    "body": "Dynamic Model Selector\nOverview\n\nThis skill analyzes user queries to recommend the optimal AI model from available GitHub Copilot options, balancing performance, cost, and task requirements.\n\nHow to Use\nProvide the user query or task description.\nRun the classification script to analyze complexity.\nChoose the suggested model or adjust based on preferences.\nClassification Criteria\nSimple tasks (short responses, basic chat): Use faster, free models like grok-code-fast-1.\nComplex reasoning (analysis, multi-step): Use advanced models like gpt-4o or claude-3.5-sonnet.\nCode generation: Prefer code-optimized models.\nCost sensitivity: Favor free models when possible.\nExample Usage\n\nFor a query like \"Explain quantum computing\": Classify as medium complexity -> Recommend gpt-4o.\n\nFor \"Write a Python function to sort a list\": Classify as code task -> Recommend grok-code-fast-1.\n\nResources\nscripts/\nclassify_task.py: Analyzes the query and outputs model recommendation.\nreferences/\nmodels.md: Detailed list of available models, pros/cons, costs."
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    "provenanceUrl": "https://clawhub.ai/mpelissari/dynamic-model-selector",
    "publisherUrl": "https://clawhub.ai/mpelissari/dynamic-model-selector",
    "owner": "mpelissari",
    "version": "1.0.0",
    "license": null,
    "verificationStatus": "Indexed source record"
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