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

Annotations already cover readOnlyHint=true and destructiveHint=false, so safety is established. The description adds meaningful behavioral detail: a cost of $1.00 USDC per call, a signed ML-DSA-65 receipt anchored on Base, and that it operates on 'live web sources.' This goes beyond the annotations and helps the agent understand side effects (payment) and output guarantees.

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 three short sentences that front-load the core purpose ('web research synthesis') and the key differentiator (cryptographic receipt). The cost is stated succinctly. There is no fluff or redundancy; every sentence carries distinct 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 single-parameter, read-only tool with no output schema, the description provides adequate context: what it does, what input is expected, what the output includes (synthesis + signed receipt), and the cost. The term 'governed' is ambiguous and could be clarified, but overall the tool is sufficiently described for an agent to call it correctly.

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?

With 0% schema description coverage, the description must clarify the parameter's meaning. It states the agent submits 'a research question,' which correctly identifies the semantic role of the 'question' parameter. However, it does not elaborate on expected phrasing, constraints, or examples beyond what the schema implies, leaving room for ambiguity.

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 the tool does web research synthesis: 'returns an AI synthesis across live web sources.' It is specific about the resource (web sources) and the unique differentiator (cryptographic receipt). This distinguishes it from sibling synthesis tools like get_company_intelligence_synthesis or get_regulatory_news_synthesis, which are domain-specific.

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 implies usage: 'Agent submits a research question' suggests a general research use case. However, it does not explicitly say when to choose this over other synthesis siblings or provide exclusions. The mention of 'governed' and the receipt hints at auditability use cases, but this is not made explicit.

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