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

With no annotations, the description carries the full burden. It discloses key behavioral outputs: when the claim was observed, whether it expired, and what replaced it. However, it does not state whether the operation is read-only, how expiry is determined, or what data source is consulted, leaving meaningful gaps.

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 compact and front-loaded with the core question, then quickly lists the return information. The final sentence about training data adds useful context rather than padding. Slightly more structure around parameter expectations would improve it, but no words are wasted.

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 core purpose and primary returns are clear, and the tool appears simple. However, with no output schema, no annotation safety profile, and no explanation of `outlet` or expiry semantics, an agent lacks some details needed for robust invocation. It is adequate but not fully complete.

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 only 50%; `query` is described but `outlet` has no description. The tool description does not explain `outlet` or clarify how it relates to the query, so it fails to compensate for the undocumented parameter. It mostly restates what the schema already says about `query`.

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 states a specific operation: checking whether a remembered claim about a programme is still current, and it names concrete return content (observation time, expiry status, replacement). It does not explicitly contrast sibling tools like media_freshness or media_verify, but the 'model training data' framing makes the purpose fairly distinctive.

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?

Usage is implied through the question 'Is a remembered claim about a programme still current?' and the note about a model's training data, but there are no explicit when-to-use or when-not-to-use instructions and no alternatives are named. An agent can infer context but gets no routing guidance.

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