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

Goes well beyond the annotations: discloses the exact clustering algorithm (overlap coefficient on normalized headline tokens, 0.40 threshold, ≥3 shared tokens, single-linkage), that article text is never read, that singletons are counted but not returned, and the full x402 payment procedure including the challenge/retry at _meta["x402/payment"]. readOnlyHint=false is consistent with a paid call rather than a data mutation.

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 what the tool returns and how it is computed, with caveats (not GDELT-reported, singletons excluded) placed before the call instructions. Dense but every sentence carries signal; the HTTP endpoint mention is the one marginally expendable item.

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?

With no output schema, the description still tells the agent what it gets back (clusters, counted singletons, articles_considered) and what the cost and payment path are. It stops short of describing the shape of a returned cluster (members, domains, timestamps), which would fully close the gap.

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 `limit` is documented in the schema. The description explains what the article pool is over and that the pool size is reported as articles_considered, but leaves `q` (GDELT query syntax) and `days` (defaults/limits) uninterpreted, so it only partially compensates for the coverage gap.

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?

Names a specific verb and resource — deterministic same-story headline clustering computed by this service over a GDELT query pool — and explicitly separates itself from GDELT-reported groupings and from sibling news tools. An agent can tell exactly what it produces versus gdelt_news_crypto or news_search.

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?

Explicitly routes the agent to gdelt_news_clusters_preflight first to check story counts for free, and states the per-call price and payment flow before use. It does not state when to prefer the plain news tools over clustering, but the preflight alternative covers the main decision point.

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