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Glama

summarize_network

Read-only

Compute degree, role composition, self-loops, and connectivity of an extracted regulatory subnetwork, clarifying that structural position does not establish disease-driving status.

Instructions

计算已提取子网络的度数、角色组成、自环、连通性;结构地位不等于疾病驱动性。

Input Schema

NameRequiredDescriptionDefault
subnetwork_idYes
include_self_loopsNo

Output Schema

NameRequiredDescriptionDefault
dataYes
errorNo
statusYes
coverageYes
warningsNo
provenanceYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.3/5.0
Behavior3/5

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

Annotations already declare this is a read-only, non-open-world operation, so the safety profile is covered. The description adds the calculated metrics and an interpretive caution that structural position is not disease driverness, but it does not explain how include_self_loops affects behavior or how invalid subnetwork_id values are handled.

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 single compact sentence that front-loads the computation targets and adds a useful interpretive caveat with no wasted text. Every part contributes to purpose or interpretation.

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?

The output schema exists, so the description need not enumerate return fields, and the annotations cover read-only behavior. However, with 0% schema description coverage, the definition remains incomplete on parameter behavior and explicit usage sequencing.

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

Parameters2/5

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

Schema description coverage is 0%, so the description should compensate for both parameters. It only hints at self-loops via '自环' and says nothing about the required subnetwork_id or how include_self_loops changes the computation, leaving parameter meaning largely undocumented.

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 uses a clear verb-resource combination: it computes degree, role composition, self-loops, and connectivity for an already extracted subnetwork. It distinguishes itself from extraction/export siblings by emphasizing summarization of an existing subnetwork, though it does not explicitly name those siblings.

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?

The phrase '已提取子网络' implies this should be used after a subnetwork has been extracted, but it never explicitly says to use extract_subnetwork first or when not to use this tool. Usage is therefore implied rather than clearly guided.

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