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hjlrosales

EPANET MCP Server

by hjlrosales

set_pipe_diameter

Update a pipe's diameter in an EPANET network, validating the change against engine rules. Invalidates prior simulation results, so re-run the simulation afterward.

Instructions

Change the diameter of a pipe in a loaded network. The edit is validated against the EPANET engine before it is applied: the pipe must exist and be a pipe, the value must be within realistic bounds for the model's units, and the edited model must re-parse with the requested diameter. Previous simulation results for the network are invalidated (they describe the old model) — re-run run_simulation afterwards.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
linkIdYesId of the pipe to resize (use get_links to list pipe ids).
diameterYesNew diameter in the model's native units (mm for SI models, inches for US-unit models). Realistic bounds are enforced: 1–10000 mm or 0.01–400 inches.
networkIdYesThe network id returned by load_network.
Behavior4/5

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 covers validation (pipe exists, is a pipe, value within realistic bounds), the requirement that the edited model re-parse, and the side effect of invalidating previous simulation results. It stops short of describing the exact error handling or return value, but the key behavioral traits are transparent.

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 dense sentence that packs the core action, validation rules, and side effect clearly. It front-loads the primary purpose and uses no filler. Every clause contributes essential information.

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

Completeness4/5

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

For a mutation tool with no output schema, the description covers the essential aspects: what it does, the validation constraints, and the invalidation of simulation results with a follow-up suggestion. It could mention the exact failure behavior or response format, but given the tool's simplicity and the schema coverage, this is largely complete.

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?

The input schema already provides 100% coverage with descriptions for all three parameters, including units and realistic bounds for diameter. The description adds contextual value (e.g., that the pipe must exist and be a pipe, and that validation occurs), but it does not add new parameter-level semantics beyond the schema. Since schema coverage is high, a baseline of 3 is appropriate.

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 opens with a precise verb and resource: 'Change the diameter of a pipe in a loaded network.' It clearly distinguishes this from sibling tools (e.g., set_junction_demand, set_pump_speed) by targeting pipe diameter specifically, and preemptively clarifies that the target must be a pipe, not just any link.

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 provides clear context for when to use this tool: after loading a network, and it explicitly states that previous simulation results are invalidated and that run_simulation should be re-run afterwards. This gives the agent a concrete follow-up action. It does not explicitly mention alternatives, but the sibling tools are distinct enough that not naming them is acceptable.

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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