gdelt_trending

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

Annotations already declare readOnly, idempotent, openWorld and non-destructive, so the safety profile is covered. The description adds the output vocabulary (surging/rising/stable/declining/fading) and volume-over-time shape, but says nothing about data latency, coverage limits, or what happens with sparse results.

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?

Two sentences, zero filler, and the core purpose is front-loaded before the return-value detail. Nothing repeats the schema or annotations.

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 usefully states the classification categories and that volume time series is returned. However, it omits the default time window, the thresholds separating classifications, and the granularity of the volume series — details an agent needs to interpret results.

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%, so the schema already documents query, timespan and sourcelang. The description adds no interpretation of parameters — notably no default timespan or how timespan interacts with the trend classification window.

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 ('Check whether a topic is trending in global news using GDELT article volume timelines') and enumerates the output classification. It is distinguishable from gdelt_tone_analysis and gdelt_news_search by focus on trend classification, though it never names 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?

Usage is only implied: 'check whether a topic is trending' suggests a yes/no trend question rather than a retrieval task. No explicit when-to-use-this-vs-gdelt_news_search or gdelt_tone_analysis guidance, and no stated prerequisites such as the freshness of GDELT data.

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