run_model

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

Discloses that results are stored in the registry and returned as a bounded summary, but does not specify mutation side effects, re-run safety, or error behavior. With no annotations, more detail would be beneficial.

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?

Well-structured with sections, no unnecessary words. Each sentence adds value: purpose, prerequisites, side effect, and return type are concisely stated.

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?

Covers prerequisites, side effects, and return type for a simulation run tool. However, lacks details on error handling and validation of model existence. Given the complexity, it is fairly complete.

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 coverage is 0%, so description must compensate. For model_id, it only repeats 'Id of the model to run.' For timeout, it adds default unit and value. This provides minimal added meaning beyond the schema.

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 'Run the CFAST simulation for a model and summarize the outputs.' This provides a specific verb, resource, and outcome, effectively distinguishing it from sibling tools like get_results or create_model.

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?

Describes prerequisites (CFAST executable) and post-conditions (results stored for get_results), giving context for when to run. However, lacks explicit exclusions or comparisons to alternatives beyond mentioning get_results.

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