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

Annotations only cover the safety profile (readOnly, openWorld, non-destructive), and the description goes well beyond them: price ($0.006 USDC per call), payment rails and x402 auto-pay clients, the grading model (Claude Haiku 5.5 from headlines and snippets only), the 7-day/25-article ceiling, and the free-if-<2-articles rule. These are exactly the operational facts an agent needs before spending money.

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 purpose, then return shape, then cost/mechanics — a sensible order with little repetition. It is a dense block of pricing and coverage detail in a single paragraph, which is heavier than strictly needed but each clause carries usable 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?

There is no output schema, and the description fully compensates by enumerating the return fields (label, -1..1 score, positive/neutral/negative counts, 3-5 themes, two-sentence summary, per-article sentiment/title/source/date/URL). Combined with the payment and coverage disclosure, an agent can call this correctly without further context.

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 only 33% (only 'topic' is documented), so the description must compensate. It partially does: 'up to 25 recent articles' conveys the limit ceiling and the example shows limit=8. However the 'category' enum (general/tech/business/science/health/politics) and the default/minimum for limit are never explained.

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 ('finds up to 25 recent articles ... and rates how the coverage reflects on the topic') plus the data scope (own news index, GDELT and Hacker News, last 7 days). The sentiment-rating capability cleanly separates it from plain news_search/crypto_news siblings without needing to name them.

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?

Names the contexts it serves ('For trading signals, brand monitoring and research agents') and gives a concrete entry path via the free-sample call. It stops short of explicit when-not-to-use guidance or naming an alternative tool (e.g. news_search for raw articles), so no alternatives are offered.

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