Skip to main content
Glama

search_by_indication

Read-only

Find drugs approved for a given medical condition by searching US FDA labeling and verifying availability in UK eMC.

Instructions

Find drugs approved for a medical condition. Searches US FDA labelling for the condition, then checks UK (eMC) availability for each drug found.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
conditionYesMedical condition or indication to search for (e.g., 'type 2 diabetes', 'hypertension')
maxResultsNoMaximum number of drug results to return

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.5.1

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is clear. The description adds behavioral detail by explaining the two-step process: searching US FDA labelling first, then checking UK (eMC) availability. This gives the agent insight into how results are derived, which is valuable beyond the annotations.

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

Conciseness5/5

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

The description is two sentences with no fluff. The first sentence front-loads the core purpose, and the second explains the process. Every word earns its place, making it highly concise and well-structured.

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

Completeness4/5

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

For a simple search tool with two parameters and read-only annotations, the description is quite complete. It covers the purpose and the process, and the annotations cover safety. It does not describe the exact output format, but with no output schema, that omission is acceptable given the tool's simplicity.

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

Parameters3/5

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

The input schema covers 100% of parameters with descriptions for both 'condition' and 'maxResults'. The description does not add additional parameter context, but since the schema already provides adequate semantics, a baseline score of 3 is appropriate.

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

Purpose5/5

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

The description clearly states the tool's purpose: 'Find drugs approved for a medical condition.' It specifies the verb 'Find' and the resource 'drugs approved for a medical condition,' and further distinguishes its approach by mentioning the US FDA labelling search and UK (eMC) availability check, which sets it apart from sibling tools like search_pubmed or get_uspi.

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

Usage Guidelines4/5

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

The description provides clear context on when to use the tool: when seeking drugs approved for a condition, with the dual FDA/eMC scope. However, it does not explicitly name alternative tools or provide exclusion criteria (e.g., 'for literature use search_pubmed'), so the guidance is strong but not fully explicit.

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