run_prover

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

With no annotations, the description must disclose behavioral traits. It only mentions automation and a 5-step workflow but omits critical details like whether it overwrites existing processes, required resources, or side effects. The agent is left guessing about safety and impact.

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 short but includes marketing fluff (emoji, bold). It is not efficiently structured: it front-loads promotional language instead of crucial operational details. Could be more concise and informative.

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 prover execution tool with 4 parameters and many siblings, the description is extremely inadequate. It does not explain the workflow, expected outputs, error states, or configuration prerequisites. An agent cannot reliably use this tool based solely on the description.

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 baseline is 3. The description adds no extra meaning beyond parameter descriptions; it does not elaborate on parameter usage or dependencies. No additional value provided.

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 automates prover setup and execution to earn tokens, using a 5-step workflow. It distinguishes from siblings by being the 'one-click' solution, but doesn't explicitly differentiate from similar tools like create_prover or stop_prover.

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?

No guidance on when to use this tool versus alternatives. The description lacks context on prerequisites, whether creation must be done first, or when to use calibration tools. Agents have no basis for selection.

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