query_signals

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

Annotations already declare readOnlyHint=true, so the description correctly aligns with that. It adds behavioral context beyond the annotations by disclosing the cost (3 tokens per call, charged to the API key owner) and the nature of the data (AI-enriched with severity/GEOINT scores and satellite-collection recommendations). There is no contradiction with annotations.

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?

The description is a single paragraph that front-loads the main purpose and key filters. It is concise at about 50 words, with no wasted sentences. However, it could be slightly more structured (e.g., bullet points for filter categories) to improve scannability.

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?

Given the tool has 16 parameters (0 required), 100% schema coverage, no output schema, and no nested objects, the description adequately covers the input domain. However, it does not mention pagination behavior (despite a cursor parameter) or the default output format. The return structure is left implicit, which may cause uncertainty for the agent.

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 baseline is 3. The description mentions the key filter groups (bounding box, date window, category) but adds only contextual value about the signals, not about parameter syntax or advanced usage. The schema already thoroughly documents each parameter, so the description does not significantly enhance parameter understanding.

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?

The description uses a specific verb ('Query') and a precise resource ('geolocated world event signals'), further elaborating on the nature of these signals (Delta Signals: geopolitical, security, disaster, infrastructure). It distinguishes itself from siblings like query_hotspots by focusing on signals and listing unique filters like bounding box, date window, and category.

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?

The description states what the tool does but provides no guidance on when to use it versus alternatives. Siblings like query_hotspots or ask_analyst are not mentioned, and no conditions for or against use are given. The cost in tokens is noted, but this is a policy detail, not usage guidance.

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