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        "label": "New install",
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      },
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  "documentation": {
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    "primaryDoc": "SKILL.md",
    "sections": [
      {
        "title": "Setup",
        "body": "On first use, read setup.md for activation preferences, credential verification, and default workflow setup."
      },
      {
        "title": "When to Use",
        "body": "User needs to build, integrate, or troubleshoot Groq API inference for chat, tool calling, or speech transcription. Agent handles request shaping, model routing, failure recovery, and safe production patterns."
      },
      {
        "title": "Architecture",
        "body": "Memory lives in ~/groq-api/. See memory-template.md for structure.\n\n~/groq-api/\n├── memory.md           # Status, activation preference, and defaults\n├── requests/           # Reusable payload snippets\n├── logs/               # Optional debug snapshots\n└── experiments/        # Prompt/model A-B notes"
      },
      {
        "title": "Quick Reference",
        "body": "Use these files as decision aids, not as static docs: pick the smallest file that resolves the current blocker.\n\nTopicFileSetup processsetup.mdMemory templatememory-template.mdRequest patternsapi-patterns.mdModel routingmodel-selection.mdFailures and recoverytroubleshooting.md"
      },
      {
        "title": "1. Verify Auth and Endpoint Before Any Work",
        "body": "Check GROQ_API_KEY first and use Authorization: Bearer $GROQ_API_KEY for every request. Use https://api.groq.com/openai/v1 as the base URL and confirm access with /models.\n\ncurl -s https://api.groq.com/openai/v1/models \\\n  -H \"Authorization: Bearer $GROQ_API_KEY\" | jq '.data[0].id'"
      },
      {
        "title": "2. Start with a Minimal Deterministic Payload",
        "body": "Begin with small prompts and explicit format instructions. Add complexity only after the baseline call is stable."
      },
      {
        "title": "3. Route by Task, Not by Habit",
        "body": "Use separate model choices for:\n\nFast interactive chat\nHigh-accuracy reasoning\nSpeech transcription\n\nChoose from live /models output instead of hardcoding assumptions."
      },
      {
        "title": "4. Design for Retry and Degradation",
        "body": "For 429 and 5xx, retry with exponential backoff and capped attempts. If a model is overloaded, fail over to a compatible backup model and log the swap."
      },
      {
        "title": "5. Validate Output Before Downstream Actions",
        "body": "If output feeds code execution or data writes, enforce JSON schema or strict parsing before acting. Reject malformed output early."
      },
      {
        "title": "6. Treat Speech as a Separate Reliability Path",
        "body": "Speech uploads have different failure modes than chat. Validate input format, check file size, and surface transcription confidence when available."
      },
      {
        "title": "7. Keep Secrets and User Data Scoped",
        "body": "Never store API keys in files. Keep request logs sanitized and avoid persisting full sensitive prompts unless the user explicitly asks."
      },
      {
        "title": "Common Traps",
        "body": "Using stale model IDs copied from old examples -> call /models and select available IDs at runtime.\nSending giant prompts without truncation -> latency spikes and timeout risk.\nIgnoring 429 backoff guidance -> repeated failures under load.\nMixing chat and transcription assumptions -> wrong endpoint and payload format.\nTrusting free-form text for automation -> parse and validate before executing."
      },
      {
        "title": "External Endpoints",
        "body": "All network traffic should be limited to these Groq endpoints for explicit inference tasks requested by the user.\n\nEndpointData SentPurposehttps://api.groq.com/openai/v1/modelsNone (GET)Discover available modelshttps://api.groq.com/openai/v1/chat/completionsPrompt messages and optionsChat completionshttps://api.groq.com/openai/v1/audio/transcriptionsAudio file and transcription paramsSpeech-to-text\n\nNo other data is sent externally."
      },
      {
        "title": "Security & Privacy",
        "body": "Data that leaves your machine:\n\nPrompt content sent to Groq inference endpoints\nAudio content sent to Groq transcription endpoint when requested\n\nData that stays local:\n\nWorkflow preferences in ~/groq-api/memory.md\nOptional local debug notes in ~/groq-api/logs/\n\nThis skill does NOT:\n\nStore GROQ_API_KEY in project files\nAccess files outside ~/groq-api/ for persistence\nCall undeclared third-party endpoints\nModify itself or other skills"
      },
      {
        "title": "Trust",
        "body": "By using this skill, prompts and optional audio content are sent to Groq.\nOnly install if you trust Groq with that data."
      },
      {
        "title": "Related Skills",
        "body": "Install with clawhub install <slug> if user confirms:\n\napi — reusable REST patterns, auth, and error handling\nmodels — model comparison and selection heuristics\nai — current AI landscape checks before implementation decisions\nfine-tuning — adaptation workflows when prompting is not enough\nlangchain — orchestration patterns for multi-step LLM pipelines"
      },
      {
        "title": "Feedback",
        "body": "If useful: clawhub star groq-api\nStay updated: clawhub sync"
      }
    ],
    "body": "Setup\n\nOn first use, read setup.md for activation preferences, credential verification, and default workflow setup.\n\nWhen to Use\n\nUser needs to build, integrate, or troubleshoot Groq API inference for chat, tool calling, or speech transcription. Agent handles request shaping, model routing, failure recovery, and safe production patterns.\n\nArchitecture\n\nMemory lives in ~/groq-api/. See memory-template.md for structure.\n\n~/groq-api/\n├── memory.md           # Status, activation preference, and defaults\n├── requests/           # Reusable payload snippets\n├── logs/               # Optional debug snapshots\n└── experiments/        # Prompt/model A-B notes\n\nQuick Reference\n\nUse these files as decision aids, not as static docs: pick the smallest file that resolves the current blocker.\n\nTopic\tFile\nSetup process\tsetup.md\nMemory template\tmemory-template.md\nRequest patterns\tapi-patterns.md\nModel routing\tmodel-selection.md\nFailures and recovery\ttroubleshooting.md\nCore Rules\n1. Verify Auth and Endpoint Before Any Work\n\nCheck GROQ_API_KEY first and use Authorization: Bearer $GROQ_API_KEY for every request. Use https://api.groq.com/openai/v1 as the base URL and confirm access with /models.\n\ncurl -s https://api.groq.com/openai/v1/models \\\n  -H \"Authorization: Bearer $GROQ_API_KEY\" | jq '.data[0].id'\n\n2. Start with a Minimal Deterministic Payload\n\nBegin with small prompts and explicit format instructions. Add complexity only after the baseline call is stable.\n\n3. Route by Task, Not by Habit\n\nUse separate model choices for:\n\nFast interactive chat\nHigh-accuracy reasoning\nSpeech transcription\n\nChoose from live /models output instead of hardcoding assumptions.\n\n4. Design for Retry and Degradation\n\nFor 429 and 5xx, retry with exponential backoff and capped attempts. If a model is overloaded, fail over to a compatible backup model and log the swap.\n\n5. Validate Output Before Downstream Actions\n\nIf output feeds code execution or data writes, enforce JSON schema or strict parsing before acting. Reject malformed output early.\n\n6. Treat Speech as a Separate Reliability Path\n\nSpeech uploads have different failure modes than chat. Validate input format, check file size, and surface transcription confidence when available.\n\n7. Keep Secrets and User Data Scoped\n\nNever store API keys in files. Keep request logs sanitized and avoid persisting full sensitive prompts unless the user explicitly asks.\n\nCommon Traps\nUsing stale model IDs copied from old examples -> call /models and select available IDs at runtime.\nSending giant prompts without truncation -> latency spikes and timeout risk.\nIgnoring 429 backoff guidance -> repeated failures under load.\nMixing chat and transcription assumptions -> wrong endpoint and payload format.\nTrusting free-form text for automation -> parse and validate before executing.\nExternal Endpoints\n\nAll network traffic should be limited to these Groq endpoints for explicit inference tasks requested by the user.\n\nEndpoint\tData Sent\tPurpose\nhttps://api.groq.com/openai/v1/models\tNone (GET)\tDiscover available models\nhttps://api.groq.com/openai/v1/chat/completions\tPrompt messages and options\tChat completions\nhttps://api.groq.com/openai/v1/audio/transcriptions\tAudio file and transcription params\tSpeech-to-text\n\nNo other data is sent externally.\n\nSecurity & Privacy\n\nData that leaves your machine:\n\nPrompt content sent to Groq inference endpoints\nAudio content sent to Groq transcription endpoint when requested\n\nData that stays local:\n\nWorkflow preferences in ~/groq-api/memory.md\nOptional local debug notes in ~/groq-api/logs/\n\nThis skill does NOT:\n\nStore GROQ_API_KEY in project files\nAccess files outside ~/groq-api/ for persistence\nCall undeclared third-party endpoints\nModify itself or other skills\nTrust\n\nBy using this skill, prompts and optional audio content are sent to Groq. Only install if you trust Groq with that data.\n\nRelated Skills\n\nInstall with clawhub install <slug> if user confirms:\n\napi — reusable REST patterns, auth, and error handling\nmodels — model comparison and selection heuristics\nai — current AI landscape checks before implementation decisions\nfine-tuning — adaptation workflows when prompting is not enough\nlangchain — orchestration patterns for multi-step LLM pipelines\nFeedback\nIf useful: clawhub star groq-api\nStay updated: clawhub sync"
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    "owner": "ivangdavila",
    "version": "1.0.0",
    "license": null,
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