{
  "ok": true,
  "manifest": {
    "schema_version": "evercraft.enterprise_ops.capabilities.v1",
    "product": "BuildFlow",
    "product_role": "Standalone enterprise-operations product",
    "status": "r_and_d_shadow_mode",
    "positioning": "Evidence-native, coexistence-first operating layer that can ingest messy business data, reconstruct processes, surface uncertainty, route human decisions, and prepare bounded actions without requiring immediate system replacement.",
    "safety_model": {
      "public_discovery": true,
      "private_customer_data": false,
      "external_writes_default": false,
      "human_confirmation_for_material_actions": true,
      "evidence_preserved": true,
      "unknown_is_not_false_or_zero": true
    },
    "capabilities": [
      {
        "id": "shadow_import",
        "title": "Shadow import and evidence preservation",
        "solves": [
          "I have CSV or exported business data an AI cannot safely normalize",
          "I need to understand a messy operational dataset before migration",
          "I need provenance-preserving import without overwriting the source"
        ],
        "accepts": [
          "csv",
          "structured exports",
          "connector-fed records"
        ],
        "produces": [
          "SourceRecord",
          "ImportRun",
          "ImportConflict",
          "mapping preview"
        ],
        "execution": "read_only_or_shadow",
        "auth_required_for_customer_data": true,
        "live_in_product": true
      },
      {
        "id": "entity_mapping",
        "title": "Entity matching with human adjudication",
        "solves": [
          "The same vendor/customer appears differently across systems",
          "I need deduplication without risky silent merges",
          "An AI needs a safe place to resolve uncertain company identity mappings"
        ],
        "accepts": [
          "source records",
          "mapping candidates"
        ],
        "produces": [
          "MappingCandidate",
          "MappingDecision",
          "conflict evidence"
        ],
        "execution": "human_adjudicated",
        "auth_required_for_customer_data": true,
        "live_in_product": true
      },
      {
        "id": "process_discovery",
        "title": "Observed process reconstruction",
        "solves": [
          "I need to know how this company actually operates",
          "The documented workflow may not match real behavior",
          "I need recurring process and exception-path discovery from event history"
        ],
        "accepts": [
          "timestamped operational events",
          "source-system histories"
        ],
        "produces": [
          "ProcessObservation",
          "ProcessPatternCandidate",
          "normal/exception paths"
        ],
        "execution": "read_only_analysis",
        "auth_required_for_customer_data": true,
        "live_in_product": true
      },
      {
        "id": "role_work_queue",
        "title": "Role-adaptive operational work routing",
        "solves": [
          "Different teams need different views over the same process",
          "Finance, purchasing, approvers and requesters should not share one giant ERP screen",
          "An agent needs to route exceptions or decisions to the right human"
        ],
        "accepts": [
          "work items",
          "role assignments",
          "process state"
        ],
        "produces": [
          "role-specific queues",
          "next actions",
          "evidence context"
        ],
        "execution": "tenant_scoped",
        "auth_required_for_customer_data": true,
        "live_in_product": true
      },
      {
        "id": "bounded_action",
        "title": "Policy-checked bounded action preparation",
        "solves": [
          "An AI wants to act on business data without becoming the authority",
          "I need stale approvals, value thresholds and action permissions checked before execution",
          "I need idempotent, receipt-backed enterprise actions"
        ],
        "accepts": [
          "ProposedAction",
          "AuthorizationGrant",
          "Approval",
          "subject version"
        ],
        "produces": [
          "policy disposition",
          "ApprovalRequest",
          "ActionExecutionReceipt"
        ],
        "execution": "bounded_internal_only_currently",
        "auth_required_for_customer_data": true,
        "live_in_product": true,
        "external_write_status": "disabled"
      },
      {
        "id": "procure_to_pay_shadow",
        "title": "Procure-to-pay shadow reconstruction",
        "solves": [
          "I need to reconstruct request-to-approval-to-PO-to-receipt-to-invoice flow",
          "I need to find approval gaps, duplicate vendors or invoice mismatches",
          "I need an ERP migration wedge that does not replace the ledger on day one"
        ],
        "accepts": [
          "vendors",
          "purchase requests",
          "approvals",
          "POs",
          "receipts",
          "invoice references"
        ],
        "produces": [
          "process timeline",
          "exceptions",
          "recommendations",
          "reconciliation context"
        ],
        "execution": "shadow_mode",
        "auth_required_for_customer_data": true,
        "live_in_product": true
      }
    ],
    "handoff": {
      "public_route": "/agents",
      "machine_manifest": "/.well-known/evercraft-capabilities.json",
      "llm_document": "/llms.txt",
      "agent_card": "/.well-known/agent-card.json",
      "openapi": "/openapi.json",
      "discovery_function": "/functions/enterpriseOpsAgentRoute",
      "buildflow_mcp": "/functions/enterpriseOpsMcp",
      "official_evercraft_mcp": "https://evercraft-ai-suite-08c4d2b8.base44.app/api/apps/692b4178919afe7d08c4d2b8/functions/machineCommerceMcp",
      "rule": "Discovery is public. Customer data access and consequential execution require authenticated tenant context and configured authority."
    }
  }
}