generate_tokenomics_model

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

With no annotations, the description carries full burden. It notes 'Async' and the return format '{job_id, status_url}', which are key behaviors. However, it does not disclose potential side effects (e.g., resource consumption), error conditions, or how to retrieve results later. More detail is needed for full transparency.

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?

Three sentences with no filler. The first sentence states the purpose, the second gives usage constraints, the third describes the return value. Every sentence earns its place, and the critical information is front-loaded.

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 complexity of a tokenomics simulation tool with an array parameter and no output schema, the description is too minimal. It omits essential details like how to interpret the result, required data dependencies, and the full async workflow. More context is needed for an agent to use it effectively.

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 0% for 3 parameters. The description only hints at 'scenarios' but does not explain what parameters mean, their formats, or valid values. Since the description adds no parameter clarification, it fails to compensate for the lack of schema descriptions.

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 function: 'Simulate emission/unlock impact on FDV across scenarios.' This is a specific verb (simulate) and resource (emission/unlock impact on FDV), and it distinguishes the tool from the many data-retrieval siblings. No tautology or vagueness.

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 usage context: 'Async, Team tier.' This indicates it is for asynchronous simulation and intended for Team-tier users. However, it does not explicitly state when not to use this tool or suggest alternatives (e.g., get_tokenomics for simpler queries). The guidance is clear but not exhaustive.

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