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

Annotations only declare readOnlyHint=false, idempotentHint=true and destructiveHint=false; the description adds that this is a genuine discrete-event simulation rather than an AI estimate, that missing inputs fall back to defaults which are disclosed in the answer, that a simulator link is returned, and that the call costs no AI credits. Those are exactly the operational facts an agent cannot infer from the annotations.

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?

Front-loads what the tool is and what it returns, then usage triggers, then input guidance and the return/cost note. It is dense but nearly every clause carries a distinct fact; the em-dash aside about 'not an AI guess' borders on marketing but does disambiguate behavior.

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?

With six parameters, one required, no output schema and no nested objects, the description covers the input policy (defaults), the return shape (results plus a simulator link) and the cost model. Nothing an agent needs in order to call it correctly is missing.

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 100%, so per-parameter meaning is already documented; the description adds the calling strategy, telling the agent to pass whatever numbers the user supplies and rely on disclosed defaults otherwise, which explains how to handle partially specified requests. It does not elaborate on the min/max range semantics for step_minutes beyond what the schema says.

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?

States a specific verb and resource: runs a flowchart/swimlane/BPMN diagram through a discrete-event process simulator and returns cycle time, cost per case, team utilization and bottleneck with a suggestion. That output set cleanly separates it from the sibling tools, which all create, edit, render or list diagrams rather than analyze them.

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?

Gives explicit user-intent triggers: 'when the user asks how long a process takes, where it gets stuck, how many staff they need, or what happens at a given volume.' There is no when-not guidance or named alternative (e.g. use edit_diagram first if the diagram is wrong), so it falls short of the full 5.

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