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

With no annotations provided, the description carries the load. It discloses the per-call cost, behavior on feed dialects, and the polling use case. It does not mention error handling, authentication prerequisites, or rate limits, which would be beneficial, but the provided behavioral context is valuable and non-obvious.

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 efficiently structured: main purpose, benefit of normalization, usage tip, and cost are all included in about 50 words. It is front-loaded with the core action and does not waste words, though it could be slightly more compact.

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 description specifies the return shape (item fields and feed metadata) and cost, which is essential for the agent to know what to expect. It omits authentication/payment setup details and error behavior, but for a simple read tool with 3 easily understood parameters, it covers the major needs well.

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 100%, so parameters are fully documented in the schema (e.g., url, limit with defaults, since with ISO-8601). The description adds extra context for 'since' by explaining its use case for polling, which is helpful but does not significantly increase meaning beyond the schema. Baseline of 3 is appropriate.

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 verb (Fetch) and resource (RSS, RSS/RDF, Atom feed) and explains the normalization of inconsistent formats into one consistent shape. It clearly differentiates from siblings like discover_feeds or request_data by focusing on reading a known feed, not on discovery or generic data retrieval.

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?

It provides clear context for when to use the tool, such as polling with the 'since' parameter, and explicitly recommends it as 'the cheap way to poll for what changed.' However, it does not name sibling tools or state explicit conditions to prefer alternatives, though the distinct purposes make this less critical.

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