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Glama

BioCosm

by io.github.nhoverte

find_related

Find nodes connected to a given node. Three relationship types are derived on-the-fly:

  • "drug_target": for a drug, the targets it hits (and vice versa for a target node, the drugs that hit it)

  • "same_company": drugs sharing a company with this node

  • "same_target_class": drugs with the same mechanism_class

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum results per link type (default 30)
node_idYesSource node identifier
link_typeNoOptional filter — one of "drug_target", "same_target_class", "same_company". If None, returns all three groups.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4/5.0
Behavior2/5

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

With no annotations, the description carries full burden but only states that relationships are 'derived on-the-fly' and lists the types; it lacks details on side effects, error handling, rate limits, or performance implications.

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 a compact paragraph with a clear first sentence and well-organized bullet points for the three relationship types, with no unnecessary words.

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?

Given the presence of an output schema and 100% parameter coverage, the description covers the core functionality and relationship semantics, though it omits behavioral details like pagination or error scenarios.

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

Parameters4/5

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

While schema coverage is 100%, the description adds value by explaining the meaning of each link_type value (e.g., 'drug_target: for a drug, the targets it hits'), going beyond the schema's terse descriptions.

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 finds nodes connected to a given node and enumerates three specific relationship types, making its purpose distinct from sibling tools like find_by_phase or find_by_target.

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 implicitly guides usage by listing the three relationship types, but does not explicitly state when to avoid this tool or mention alternatives such as get_company_portfolio or search_nodes.

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

All BioCosm toolsInspect
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TDQS

A3.9/5.0
Disambiguation4/5

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 Consistency4/5

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.

Tool Count5/5

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.

Completeness5/5

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.

Resources