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

The description states that the tool is read-only (readOnlyHint: true is already annotated) and gives temporal scope ('over the last 30 days') and data nature (descriptive counts, not a score or judgment). It adds context beyond the annotation, explaining what the tool returns without contradicting the annotation.

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 two sentences long, front-loads the key action and entity scope, and avoids fluff. It efficiently conveys purpose, data context, and exclusions. Could be considered slightly dense but not verbose; earns a 4 for being concise and well-structured.

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 has only one parameter, complete schema coverage, and a provided output schema. The description explains the tool's purpose, data time window, and what it does not provide, making it complete for an agent to select and invoke correctly. No gaps are present given the simplicity and available structured metadata.

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 input schema documents the 'entity' parameter with examples (e.g., 'Qwen 3.8' or 'Anthropic'). The description adds meaning by clarifying the kind of entity (company, model, or person) and the context of how the data is used (provenance split). Since schema coverage is 100%, the baseline is 3, but the description provides valuable extra semantics, earning a 4.

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 purpose: for one entity (company/model/person), it shows how much claim provenance data is self-reported vs independently evaluated, over the last 30 days. It specifies the verb ('get'), resource ('entity provenance'), and distinguishes from a score or judgment, differentiating it from siblings like get_china_signal or get_topic_signal.

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 explains when to use this tool ('to answer is the buzz around X coming from X?') and clarifies what it does not do (not a score, not a judgment). It provides clear context but does not explicitly state when not to use it or list alternatives among the provided sibling tools.

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