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

The description discloses key behavioral traits beyond annotations: it emphasizes that results come from a real simulation and warns against fabrication. Annotations already indicate readOnlyHint=true, but the description adds critical context about the authenticity and handling of output data.

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?

The description is concise and front-loaded with the main purpose. It includes necessary instructions without excessive wordiness. Minor redundancy exists (e.g., 'ANTI-FABRICATION' could be more succinct) but overall well-structured.

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?

Given the tool's moderate complexity, the description is complete: it explains what the tool does, what it returns, and how to use the output correctly (verbatim quoting, re-calling for follow-ups). The output schema exists to cover return structure, so no further detail is needed.

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?

The input schema already provides 100% coverage with a description for model_id ('Which sample model to simulate') and an enum of three options. The description does not add new information about the parameter beyond mentioning 'bundled sample model' and listing the options in 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 it runs a supply-chain simulation on bundled sample models and lists the outputs (metrics, time-series, etc.). It distinguishes itself from sibling tools which are for describing or explaining demos, not running simulations.

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 provides clear guidance on when to use the tool (to get simulation results) and includes important usage instructions like quoting verbatim and re-calling for follow-ups. However, it does not explicitly state when not to use it (e.g., if the user needs a description instead).

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