Find all drugs that target a specific gene/protein.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum results (default 50, max 200) | |
| target_gene | Yes | Gene symbol or target name (e.g. "EGFR", "KRAS", "PD-1") |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It does not disclose whether the operation is read-only, any rate limits, pagination behavior, or the maximum number of results (though the input schema indicates a limit parameter). This lack of transparency could lead to incorrect usage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that front-loads the purpose. Every word is necessary, and there is no fluff or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the core purpose but lacks details on limits, sorting, or result format. While the output schema exists, the description could provide more context for effective use, especially given the number of sibling tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% (both parameters have descriptions). The tool description adds no new information beyond the schema. Per rule, baseline is 3 when coverage is high.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Find', the resource 'drugs', and the criterion 'target a specific gene/protein'. It is concise and distinct from sibling tools like 'find_by_phase' which filters by clinical phase.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention when not to use it or suggest any alternatives, despite the presence of 13 sibling tools with overlapping functionality.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Tools have mostly distinct purposes, though get_node and get_pos_score both provide probability-of-success data (get_node includes a summary, get_pos_score gives detailed factors). Descriptions clarify the difference, so confusion is minimal.
Naming follows a verb_noun pattern but mixes verbs: 'find', 'get', 'list', 'search'. Within the 'get' group, all are consistent. The mix is not chaotic and remains predictable.
13 tools cover the biomedical domain well without being excessive. Each tool has a clear purpose, from searching and listing to fetching detailed node data, statistics, and specialized reports.
For a read-only database, the tool set is complete. It supports search, filtered queries, detailed node retrieval, specialized data (PoS, freshness, staleness), and statistics. No obvious gaps for typical query needs.