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

With no annotations, the description carries the burden of behavioral disclosure. It clarifies that feed_score is about data, not hardware, and describes the trailing window and the optional machine reliability field. This gives a good sense of what the tool returns and how to interpret it, though it doesn't explicitly state that it's a read-only 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, front-loads the main purpose, and adds a clarifying note about feed_score without unnecessary detail. It's well-structured and readable.

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?

For a simple tool with one parameter and no output schema, the description covers the return contents and interpretation. It's complete enough for an agent to call the tool correctly, though it could explicitly link days to the trailing window and mention the output format.

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 mentions a 'trailing window' which implicitly maps to the 'days' parameter, but it doesn't explicitly state that 'days' controls the window length. With only one simple integer parameter and schema coverage of 0%, the description partially compensates but leaves the connection implicit.

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 what the tool does: returns a measure of each provider's data feed dependability (poll success over a trailing window) and optional machine reliability. It distinguishes itself from siblings by focusing on reliability, not market or account data, though it doesn't explicitly name an alternative.

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 what the tool measures but provides no guidance on when to use it versus other tools, nor any exclusions or prerequisites. An agent would have to infer usage from the description alone, which is insufficient.

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