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brightlikethelight

NetworkX MCP Server

maximum_flow

Analyze a directed graph to compute the maximum possible flow from a source node to a sink node considering edge capacities.

Instructions

Calculate maximum flow in a directed graph

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sinkYes
graphYes
sourceYes
capacityNocapacity
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 the operation ('calculate maximum flow') and the graph type ('directed graph'), but does not disclose return value, whether it mutates the graph, assumed graph representation, error conditions, or capacity conventions. This is a significant transparency gap for a computational algorithm.

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 concise sentence with no unnecessary words, making it front-loaded and easy to parse. However, it is arguably too terse, sacrificing critical detail for brevity, but the conciseness itself is not padded or redundant.

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

Completeness1/5

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

The tool is complex (network flow algorithm) with 4 parameters, no output schema, and no annotations. The description only provides the core verb and resource, omitting graph representation, capacity handling, return format, and any usage constraints. This is far from complete for an agent to invoke the tool correctly without additional information.

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 provides no explanation of the parameters. The schema lists graph, source, sink, and capacity, but the description does not clarify what 'graph' format is expected, what source/sink refer to, or that capacity names an edge attribute. The description adds no value to understanding the parameters.

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 specific verb 'Calculate' and identifies the resource 'maximum flow', clearly distinguishing it from sibling graph algorithms like shortest_path. However, it could be more precise by mentioning 'from source to sink' and the dependency on edge capacities, which the schema implies but the description omits.

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?

No usage context is provided. The description does not explain when to choose max flow over other algorithms, what prerequisites exist (e.g., directed graph with capacities), or mention any alternatives. The usage is only implied by the tool's name and the verb 'calculate', leaving the agent without explicit guidance.

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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