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

Beyond the annotations (readOnlyHint, etc.), the description adds crucial behavioral details: outputs include tanker events and tank-level trace, and the anti-fabrication warning that numbers come from a real engine run and must be quoted verbatim. This significantly exceeds structured 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 well-structured: it names the tool, explains the simulation model, describes the return value, and adds the anti-fabrication note. Each sentence has a distinct purpose with no wasted words.

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?

Despite having no output schema, the description specifies what is returned (tanker events, tank-level trace). It also provides the model's historical/contextual significance and the simulation's hybrid nature. This is complete for a complex demo tool with good annotations.

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 schema already provides full documentation for the single parameter 'simulation_days' (default, min, max, description). The description adds no additional parameter context or semantics, which is acceptable given 100% schema coverage.

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 tool's action: 'Run the Valdez Tanker (VALD) demo' and identifies the specific model (Koelling-Remy 1983 Alaska Pipeline). This distinguishes it from sibling run_* tools by naming the unique demo and its role.

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 gives clear context about what the demo models (continuous flow, discrete arrivals, F2I/I2F transitions) and its purpose as the 'paradigm-integration motivator', implying when it would be relevant. However, it does not explicitly contrast with other run_* tools or state when not to use it.

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