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

Goes well beyond the readOnlyHint/openWorldHint annotations: it discloses the quota (3 free calls/day across all tools), the price ($0.0025 USDC), and the exact in-band payment mechanism (params._meta["x402/payment"]). It also documents auto-discovery of feeds from HTML pages and the truncation limit for full content, which the agent cannot learn from annotations.

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?

Pricing/limit is front-loaded, then output shape, then usage routing — a sensible order with almost no waste. The middle sentence is long and comma-dense, but each clause conveys distinct API-relevant information.

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 read-only fetcher with a full output schema, the description covers inputs, filtering, optional full text, return shape, cost, and sibling routing. Nothing an agent needs to call it correctly is missing.

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 already 100%, so the baseline is 3; the description adds value by explaining filtering with since= and limit= and that include_content=true adds full text. It leaves summary_chars strictly to the schema, which is acceptable given full coverage.

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?

States a specific verb+resource: converts RSS/Atom/JSON Feed URLs (or pages that link feeds, auto-discovered) into clean normalised JSON items. It enumerates the returned fields, so the agent knows exactly what it is getting, and it is clearly distinguishable from text-extraction siblings.

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?

Has an explicit 'When to use' sentence with concrete scenarios (watch a blog, changelog, podcast, news source) and names the alternative — page-rag for full text of one article page — with the condition that selects it. No inference required.

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