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brightlikethelight

NetworkX MCP Server

matching

Compute the maximum-weight vertex pairing in a graph where each vertex is used at most once, solving optimal assignment problems.

Instructions

Find maximum weight matching in a graph

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
graphYes
max_cardinalityNo
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only states 'find', implying a read operation, but does not mention whether the graph is modified, what output format to expect, or any constraints on the input graph. This is insufficient for a tool without structured safety metadata.

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 description is a single, front-loaded sentence with no wasted words. While it is concise, it omits critical details that would be expected given the tool's complexity, but conciseness itself is strong.

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

Completeness2/5

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

This is a graph algorithm tool with two parameters, no output schema, and no annotations. The description only names the algorithm, leaving out input format, return value, and any behavioral details. Given the complexity of maximum weight matching, the description is severely incomplete for an AI agent to invoke it correctly.

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

Parameters1/5

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

Schema description coverage is 0%, and the description does not mention either 'graph' or 'max_cardinality'. It fails to explain what format 'graph' should take (e.g., adjacency list, edge list) or what 'max_cardinality' controls. The tool provides no semantic value for the parameters beyond their names.

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 'Find maximum weight matching in a graph' uses a specific verb and resource, clearly identifying the tool's purpose. It distinguishes itself from sibling graph algorithms like shortest_path and minimum_spanning_tree by naming a specific type of matching.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

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. There is no mention of prerequisites (e.g., weighted graph) or exclusions, leaving the agent to infer usage purely from the name.

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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