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

Goes well beyond annotations: discloses exactly what sources are read (vendor pages, code repository read-never-run, pricing page buttons), the answer taxonomy (yes/no/partly/unknown with quotes, URLs, observation dates), latency (~15 s), job de-duplication ('identical questions share one job'), and the epistemic caveat that findings are the vendor's own claims, not verification. The idempotentHint is confirmed by the shared-job statement rather than contradicted.

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 the 'Use when...' trigger, then behavior, then the polling fallback and the dedup caveat. Dense but every clause carries actionable information; nothing is redundant.

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?

No output schema exists, so the description carries the full burden of explaining returns, and it does: the yes/no/partly/unknown taxonomy with quotes, URLs and observation dates, plus the synchronous-vs-async timing model. Nothing an agent needs to call or interpret it 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 description coverage is 100%, so the schema already documents all three parameters. The description nonetheless adds real invocation value with concrete examples (provider_id flux_operator, requirement 'Is there a Helm chart for Kubernetes?') that show the expected granularity of a question, going slightly beyond the schema's generic examples.

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 (request product research on one listing) and pins the exact scope: one specific fact a profile does not settle. It is immediately distinguishable from get_research (polling) and search_providers (source of provider_id), which it names.

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 when-to-use condition ('buying decision hinges on one specific fact about one listing that its profile does not settle') plus the alternative path when the answer is not immediate ('otherwise call get_research with the job_id after poll_after_seconds'). Both the trigger and the fallback are spelled out.

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