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Lucas-Servi

kegg-mcp-server

by Lucas-Servi

get_compound_info

Read-onlyIdempotent

Retrieve detailed information for KEGG compounds by compound ID, with summary or full detail options.

Instructions

Get detailed information for a KEGG compound entry.

Args: compound_id: KEGG compound ID (e.g. 'C00002' for ATP, 'C00031' for D-Glucose). detail_level: 'summary' (default, compact) or 'full' (complete flat-file parse).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
compound_idYes
detail_levelNosummary

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Annotations already indicate readOnlyHint, openWorldHint, idempotentHint, and non-destructive behavior. The description adds behavioral context by explaining the detail_level parameter (summary vs full flat-file parse), which goes beyond the schema's enum. It does not contradict any 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 extremely concise—two sentences plus a two-line args block. Every sentence adds value: the first states purpose, the second provides usage guidance. No redundant or filler content.

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

Completeness5/5

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

Given the tool's simplicity (2 parameters, required compound_id, enum for detail_level) and the presence of an output schema (not shown but referenced), the description is complete. It covers parameter semantics, default behavior, and typical use examples. No gaps are apparent.

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

Parameters5/5

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

With 0% schema description coverage, the description fully compensates by providing compound_id examples (e.g., 'C00002' for ATP) and clarifying detail_level values ('summary' as default compact, 'full' as complete flat-file parse). This adds critical meaning beyond the raw schema types.

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 explicitly states the tool retrieves detailed information for a KEGG compound entry, with concrete examples like 'C00002' for ATP. This clearly distinguishes it from sibling tools like get_gene_info or get_reaction_info, which target different entity types.

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 does not explicitly state when to use this tool versus alternatives, but the tool name and context (siblings targeting different entities like genes, reactions) make it obvious. It provides examples of valid compound IDs, aiding selection, but lacks explicit exclusions or when-not scenarios.

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

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