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

Beyond readOnly/openWorld annotations, it discloses the upstream provider (Algolia HN Search, public), coverage gaps found in testing, the absence of a sentiment score, and a full billing model including price, accepted payment rails, and that failed calls are free. That is precisely the context annotations cannot carry.

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?

A single dense paragraph that front-loads the core capability before limitations and price. Every clause carries information (outputs, source limits, cost), though the price/payment-rail clause is long enough to slightly dilute the primary signal.

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 one-parameter read tool with an output schema, the description supplies everything else an agent needs: what the metrics mean, source restrictions, known failure modes from testing, and cost/charging behavior. Nothing material is left to inference.

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?

Only one parameter with 100% schema description coverage, so the schema already defines the 2–80 character constraint. The description adds the meaningful framing that the keyword is used as an HN search query driving velocity counts, but no further syntax or matching behavior.

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 ('keyword discussion velocity on Hacker News') and enumerates exactly what is returned: 24h story count, 7-day count, velocity ratio, and top 24h stories with points/comments. The explicit 'Only Hacker News' scope separates it from broader siblings like news_radar or viral_trending_radar.

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?

Makes the applicable context clear (measuring keyword discussion momentum over 24h vs. 7-day baseline) and explicitly rules out Reddit/Bluesky and sentiment, which prevents misapplication. It stops short of naming a specific sibling alternative to use when non-HN sources or sentiment are needed.

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