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三域医研 · 科研算法引擎 (SanYu Research Engine)

Protein enrichment / 蛋白富集分析

protein_enrichment
Read-only

Protein enrichment / 蛋白富集分析 | USE WHEN: GO/KEGG enrichment for a protein list | ALIASES: 蛋白富集, protein enrichment, 蛋白GO, 蛋白通路 | RETURNS: 富集通路

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": {
      "protein_list": "<protein_list>"
    },
    "name": "protein_enrichment"
  }
}

Input Schema

NameRequiredDescriptionDefault
speciesNo物种
protein_listYes蛋白列表
enrichment_typeNoGO/KEGG/Reactome

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is covered by structured data. The description adds only "RETURNS: 富集通路", which is vague and does not say what fields the enrichment table contains, how many pathways come back, or whether a background/universe is applied. Species handling and default enrichment_type are unaddressed.

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

Conciseness4/5

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

The pipe-delimited keyword block is front-loaded and compact, with the use case stated before the returns hint. The aliases line is redundancy for an English agent but plausibly aids matching of Chinese-language queries; nothing is verbose.

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?

For a simple three-parameter, read-only analysis tool with full schema coverage and no output schema, the definition covers the essentials. It still omits the return shape and whether enrichment_type defaults to GO or KEGG, which matters when the caller leaves that parameter empty.

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?

Schema description coverage is 100%, so all three parameters are already documented in the schema, and the description adds no syntax, format, or default information beyond it. Mentioning GO/KEGG loosely overlaps the enrichment_type parameter but adds no new meaning.

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 states a specific analysis (GO/KEGG enrichment) on a specific input (a protein list), which is enough for an agent to know what the tool produces. It does not differentiate from the closely related sibling go_kegg_enrichment, so an agent choosing between gene-level and protein-level enrichment gets no help.

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?

"USE WHEN: GO/KEGG enrichment for a protein list" gives one positive trigger condition, which is better than nothing. There is no when-not guidance, no prerequisite (e.g. species requirement), and no mention of the sibling go_kegg_enrichment as the alternative for gene lists.

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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