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trajectory

station__td-screen__trajectory external (needs EXECUTION_BACKEND_URL) td-screen non-pv Constructa Configa

Project tardive dyskinesia risk trajectory over time for a patient profile. Shows how irreversibility score, recovery capacity, and supersensitivity evolve month by month, and when the critical boundary is crossed.

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	`td`
family	`mcp-tool-config`

Characteristics:

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

Input schema

drug_class stringrequired — Drug class: typical_high_potency, typical_low_potency, atypical, dopaminergic, antiemetic, other
age numberrequired — Patient age in years
dose_ratio number — Dose relative to standard (1.0 = standard)
prior_episodes number — Number of prior dyskinesia episodes
max_months number — Maximum projection window in months (default 60)

Example call

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

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "station__td-screen__trajectory",
    "arguments": {
      "drug_class": "",
      "age": 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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All tools (3062 live)
/api/mcp — endpoint
/AGENTS.md — agent guide
/tools/td-screen__trajectory/raw.md — this page's Markdown twin