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

Annotations already declare readOnlyHint=true, openWorldHint=true, destructiveHint=false, so the safety profile is covered. The description adds genuinely useful non-obvious context beyond that: 7-day freshness window, 15-minute update cadence, and especially the paid model ($0.0065 USDC per call via x402 on four chains, with a free sample invocation). Missing details on rate limits, error behavior, or result ranking keep it from a 5, but the cost/payment disclosure is real added value.

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 core purpose and scope, then alternatives, then params and price – a sensible order. It is a dense single block with some redundancy (params and the example input are restated after the schema already covers them), so it is not maximally tight, but nearly every sentence carries information an agent needs.

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 return-value burden and does it: it names the returned fields (title, url, source, published_at). Combined with source provenance, freshness, cost, and the free-sample path, an agent has everything needed to call it correctly and predict the response shape.

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% and each parameter already carries its own description, so the schema does the heavy lifting and baseline 3 applies. The description restates query/limit/category, adding only the max-30 ceiling and the GDELT-topic mapping for category, both of which the schema already states. The one small extra is clarifying that 'tech' puts Hacker News first, which is also in the schema, so value above baseline is minimal.

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 ('recent news articles by keyword') and immediately scopes the corpus: ~100,000 English web articles/day from GDELT plus Hacker News, last 7 days. It also names the sibling tools it is not (crypto-news, discussion-search, web-read-batch), so an agent can disambiguate without opening any 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 an explicit use case ('current events and topic monitoring') and three named alternatives with the condition that selects each: crypto-news for crypto, discussion-search for sentiment/discussion, web-read-batch for full article text. This is exactly the when/when-not/alternative structure the dimension asks for.

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