Skip to main content
Glama

verify_order_text

Not for clinical use. Orinyx checks medication claims against cited FDA label text for testing and evaluation only. Do not use its results to diagnose, treat, prescribe or make patient care decisions. Use synthetic test data only. Verify medication orders exactly as written, e.g. "warfarin 5 mg by mouth daily" (one drug per order, at most 50 orders of 500 characters). Orinyx splits each order into its dose, route and frequency claims itself, with no model, and checks each on its own, so a part it cannot read never hides one it can. Pass the text unchanged: never correct, complete or re-spell an order first. Each row names the check that produced it (beta). Orders must be synthetic test data, never real patient records or identifiers: the text is stored in the audit record.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "orders": "<orders>"
    },
    "name": "verify_order_text"
  }
}

Input Schema

NameRequiredDescriptionDefault
ordersYes
tool_nameNo
tool_versionNo
check_interactionsNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.3/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden and does substantial work: it discloses the per-claim decomposition, that a part it cannot read never hides one it can, that each output row names the producing check (beta), and that submitted text is persisted in an audit record. It omits auth requirements, rate limits, and any error/partial-failure behavior beyond the parsing note.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The safety and synthetic-data constraints are stated twice (the opening 'not for clinical use' block and the closing 'never real patient records or identifiers'), and the block is front-loaded with disclaimers before the actual purpose appears in sentence two. The format example and behavior notes earn their place, but the redundancy and stray line breaks cost clarity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return-value detail is not required, and the description covers input formatting, data policy, and the checking mechanism. However, for a 4-parameter, no-annotation tool, the unexplained `check_interactions` flag and the missing differentiation from verify_medications leave gaps an agent would need to guess around.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate, and it compensates only for `orders` — supplying an example format, the one-drug-per-order rule, and the 50-orders/500-character limits. The other three parameters, notably `check_interactions` (default false), `tool_name` and `tool_version`, are never mentioned, so an agent cannot know what toggling interaction checking does.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific verb and resource: it checks medication orders against cited FDA label text, and it discloses the mechanism (per-claim splitting into dose, route and frequency, no model). It does not name or distinguish itself from the sibling verify_medications, so an agent cannot tell from the text which of the two to call.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is real usage framing: 'for testing and evaluation only,' 'use synthetic test data only,' and 'pass the text unchanged.' But there is no explicit when-to-use-this-vs-alternatives guidance against verify_medications, export_verification, or start_a_test, and no stated prerequisites beyond the data-policy constraint.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.