run_simulation

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It discloses that the simulation stores results for later querying, which is a side effect, and describes the nature of the output (aggregate results and warnings). It stops short of explicitly stating whether the simulation mutates the network model (though 'simulation' implies it does not) or detailing error conditions, but it covers the primary behavioral traits an agent needs to call it correctly.

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

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

Two sentences with zero filler. The main purpose is front-loaded, the results are listed succinctly, and the storage side effect is stated at the end. Every clause earns its place, making this an exemplary concise definition.

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

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

For a tool with no output schema, the description names the types of results (min/max/average pressure and flow, pump energy, warnings) and notes that results are stored for downstream querying. It clearly states the prerequisite of a loaded network. It does not explicitly mention what happens on failure (e.g., if the network is invalid) or how warnings are returned, but these are minor gaps given the level of detail provided.

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

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

Schema description coverage is 100%, so both networkId and quality are already well-documented in the input schema. The description adds no additional meaning beyond what the schema provides—it mentions quality's requirement but that is already in the schema's description. Per the calibration baseline, when the schema covers all parameters, a score of 3 is appropriate unless the description offers supplementary context, which it does not.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Run', the resource 'EPANET hydraulic simulation', and the context 'for a loaded network'. It also enumerates what results are returned (min/max/average pressure and flow, pump energy, warnings) and distinguishes itself from query tools like get_node_results and get_link_results by noting that results are stored for those tools to query. This makes the purpose unmistakable and differentiates it from siblings.

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

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly states the prerequisite 'for a loaded network', implying a load before use. It also tells the agent that results are stored so that get_node_results and get_link_results can query them, which effectively indicates the appropriate complementary tools to use afterward. However, it does not explicitly say when not to use this tool or mention any alternatives for running simulations (e.g., run_candidate or optimize_network), leaving some room for ambiguity in a larger workflow.

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