estimate_ai_reward

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

Without annotations, the description reveals that the reward is client-signed and the final tier is determined by the validator, indicating that the estimate may differ from the final reward. This provides useful behavioral context beyond a simple read operation.

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 at two sentences, but the lack of parameter details means it is not as helpful as it could be. It is well-structured and front-loaded but sacrifices completeness for brevity.

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 has three required parameters and no output schema or annotations, the description is too sparse. It omits explanations of parameter semantics, return value format, and potential side effects, leaving the agent underinformed.

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 description adds no information about the three required parameters (inputTokens, outputTokens, durationSeconds). With 0% schema description coverage, the burden falls entirely on the description, which fails to explain their meaning or expected values.

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 that the tool estimates the client-signed AIPOU reward before task completion, using a specific verb ('estimate') and resource ('AIPOU reward'). It distinguishes itself from sibling tools like 'get_aipou_contract' and 'complete_ai_task' by focusing on pre-completion estimation.

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 implies usage before a task is completed but does not specify when not to use it or explicitly mention alternatives. It provides basic temporal context but lacks clear guidance on alternative tools for related purposes.

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