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

Beyond the annotations (readOnly/openWorld/idempotent), it discloses the freshness model (fresh retrieval per request unless served from a bounded cache, per-source retrieval timestamps), the auth profile (no API key, no account) and the cost model ($0.01 USDC on Base via x402, no charge when nothing is retrieved). These are exactly the behavioral facts an agent cannot get 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?

Front-loaded with purpose, then usage, then returns, then operational facts — a sensible ordering. It is slightly padded: 'Every excerpt returned is cited evidence tied to its source URL' largely restates 'structured, cited web evidence' from the first sentence.

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?

There is no output schema, and the description compensates by describing the return shape (source URLs, retrieval timestamps, excerpts, publisher/document metadata, and a supported/contradicted/mixed/inconclusive assessment). Combined with cost, cache and auth disclosure, an agent has everything needed to call and interpret it.

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 description coverage is 100%, so the schema already documents mode, urls, language, question and max_sources, including the v0.1.0 requirement of at least one URL. The description adds no parameter-level meaning (no syntax, defaults, or tradeoffs), so the baseline 3 applies.

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 opens with a concrete verb+resource: 'Fetch public web sources and return structured, cited web evidence for a question or claim.' That is specific enough to separate it from the unrelated siblings (health, sample) without ambiguity about what the tool produces.

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 enumerates clear use cases — source verification, claim verification, evidence extraction, source-grounded research, comparing sources — which tells an agent when this tool fits. It stops short of naming when NOT to use it or any alternative, so it is clear context without exclusions.

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