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run-investigation-prioritization

station__microgram__run-investigation-prioritization external (needs EXECUTION_BACKEND_URL) microgram pv-core Constructa Configa

Transbeyesian class propagation → EIG priority ranking. For a drug-event signal, determines whether to investigate directly or rely on propagated evidence from structurally similar drugs in the same class.

Taxonomy

Linnaean classification joined from the algovigilance taxonomy index via the parent config's rank.

Rank	Value
domain	`Substrata`
kingdom	`Constructa`
phylum	`Configa`
class	`station-config`
order	`microgram`
family	`mcp-tool-config`

Characteristics:

substrate: config
domain: pv
lifecycle: continuous
authority: read
compounding: producer
io: agent-request → tool-response

Input schema

source_prr numberrequired — PRR value for the source drug-event pair
signal_threshold numberrequired — PRR threshold for signal detection (typically 2.0)
transfer_weight stringrequired — Structural similarity class: same_class | high | moderate | low | none
prior_strength stringrequired — Prior evidence strength: strong | moderate | weak | unknown
uncertainty_level stringrequired — Current uncertainty: very_high | high | moderate | low
extremity_level stringrequired — Signal extremity: extreme | moderate | low
propagation_count integerrequired — Number of adjacent drugs in the class network that would benefit from this investigation

Example call

POST /api/mcp
Content-Type: application/json

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "station__microgram__run-investigation-prioritization",
    "arguments": {
      "source_prr": 0,
      "signal_threshold": 0,
      "transfer_weight": "",
      "prior_strength": "",
      "uncertainty_level": "",
      "extremity_level": "",
      "propagation_count": 0
    }
  }
}

How to invoke from a client

From any MCP-aware client, add https://algovigilance.com/api/mcp as an MCP server, then call this tool by name. From a raw HTTP client, send the JSON-RPC body above to /api/mcp.

Agent-friendly formats

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