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

Adds substantial context beyond the annotations: roughly 60-second latency, ~$0.25 default engine cost, margin billing, budget cap semantics, and the write-scope requirement. These are exactly the traits an agent needs before committing to a slow, credit-spending call. Nothing here contradicts readOnlyHint=false / destructiveHint=true / openWorldHint=true — spending irreversible credit is consistent with a non-read-only, destructive-hinted tool.

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-loads what it does and the sibling routing, then layers cost, latency, and scope. Dense semicolon-packed sentences make it efficient but slightly harder to scan; nothing is gratuitous, but the cost paragraph could be split for readability.

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?

An output schema exists, so return values needn't be explained, and the description still covers the things structured fields can't: latency, cost model, budget cap, auth scope, and the sibling alternative. Nothing an agent needs to call this 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 100%, so the baseline is 3, but the description adds real meaning: budgetUsd's default of 2 and max of 10 are restated with the spending rationale ('budgetUsd caps it'), and chargedUsd is surfaced as the cost-reporting counterpart. The 'one sharp question' framing also shapes how query should be composed.

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 and resource ('searches X live and answers what practitioners are saying') plus the output shape ('per-claim citations and engagement evidence'). It explicitly distinguishes itself from the sibling current_pulse, so an agent can pick between them without opening either schema.

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?

Gives explicit when-to-use ('learn what people say') and when-to-use-the-other ('to learn how much they say it, use current_pulse'), plus a usage constraint ('ask one sharp question') driven by its slowness and cost. Exclusions and the alternative are both named.

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