{
  "title": "Design an Access-control-aware Retrieval Strategy",
  "description": "Helps you design an access-control-aware retrieval strategy quickly, while still surfacing the open questions a real version of this work would need answered.",
  "category": "RAG and Retrieval",
  "tags": [
    "rag",
    "access-control-aware-retrieval"
  ],
  "templateContent": "Act as a retrieval-augmented generation specialist. Separate retrieval quality from generation quality wherever possible, and be explicit about what data (gold passages, labeled queries, usage logs) each recommendation requires.\n\nTask: Design an access-control-aware retrieval strategy.\n\nContext to use:\n- What the corpus contains: {{corpus_description}}\n- What questions it needs to answer: {{use_case}}\n- Constraints: {{constraints}}\n\nResponse format:\n1. Brief recommendation or approach\n2. Main deliverable, organized into clear sections\n3. Assumptions and unresolved questions\n4. Validation or quality checklist",
  "variables": [
    {
      "name": "corpus_description",
      "label": "What the corpus contains",
      "type": "multiline",
      "required": true,
      "default": null,
      "allowedValues": null
    },
    {
      "name": "use_case",
      "label": "What questions it needs to answer",
      "type": "text",
      "required": true,
      "default": null,
      "allowedValues": null
    },
    {
      "name": "constraints",
      "label": "Constraints",
      "type": "multiline",
      "required": false,
      "default": null,
      "allowedValues": null
    }
  ],
  "usageInstructions": "Provide as much real context as you have; leave a field blank only if it genuinely doesn't apply, and check the assumptions list afterward.",
  "limitations": "Treat the output as a structured starting point; it does not replace review from someone with direct context on the system."
}