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

With no annotations provided, the description carries full weight and does so thoroughly. It discloses the computation sources, Ed25519 signing, rate-limit cost, 1-hour caching, latency behavior, and edge cases like 'available:false' and a 'truncated' flag. This is far beyond a minimal disclosure.

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 well-structured with clear sections: overview, use cases, return values, cost, and latency. It is front-loaded with the core purpose and then provides detailed but relevant specifics. Every sentence contributes useful operational or semantic context, and the formatting aids readability.

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?

The tool is complex, has no output schema, and no annotations, yet the description fully covers what the tool returns, how the numbers are sourced and signed, what edge cases to expect, cost implications, and latency. An agent has enough context to select and invoke this tool correctly and interpret its results.

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 tool has zero parameters and an empty schema description, so there are no parameter semantics to explain. Per the rubric, a zero-parameter tool gets a baseline of 4; the description instead focuses on output fields and operational behavior, which is appropriate and valuable.

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: it returns live traction numbers (usage, receipts, revenue, attestation) computed from specific owned sources. It includes concrete data fields and is easily distinguishable from sibling tools, which focus on registries, compliance, receipts, or signals rather than aggregate usage/payment metrics.

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 explicitly says when to use the tool ('when you are evaluating whether anyone actually uses and pays for this API' and 'when you need a signed, re-checkable statement'). It does not explicitly describe when not to use it or name alternative tools, so it narrowly misses a 5.

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