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

Annotations already declare readOnlyHint=true and idempotentHint=true, and the description adds useful context: the tool takes no arguments, returns only a headline rather than full details, and deliberately omits a cohort claim for Europe. This gives the agent a clear behavioral expectation beyond the safe-read annotation.

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?

Two purposeful sentences: the first states the action and scope, the second gives usage guidance and drill-down paths. No wasted words, well front-loaded.

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 zero-parameter, no-output-schema tool, the description is complete: it states the purpose, enumerates the covered markets, clarifies precision ('headline' vs full record), and names the sibling tools for deeper access. No important gap remains.

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 tool has zero parameters, so the baseline is 4. The description reinforces 'Takes no arguments' and adds meaning by specifying exactly which markets and diagnostic types are covered, which is the only relevant semantic context.

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 uses the specific verb 'Read' and resource 'historical-evidence headline' with three markets enumerated, clearly distinguishing this from sibling drill-down tools (evidence_india, evidence_us, evidence_europe). It explicitly frames this as the entry-point 'headline' view, which differentiates it from the 'full record' tools.

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?

Explicit guidance is provided: 'Start here when asked what LiquiLens has tested, then drill into evidence_india, evidence_us or evidence_europe for the full record behind each headline.' This states when to use and names the alternatives, plus notes the Europe limitation ('deliberately no cohort claim').

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