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

The annotation readOnlyHint=true already signals a safe read operation, and the description adds a critical caveat: 'invisible' means zero pickup in the Western feeds Horizon tracks, not a claim about all media. This prevents misinterpretation of the results. While it doesn't disclose rate limits or response format, the read-only nature and the scope clarification make it adequately transparent.

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 moderately sized and front-loads the core purpose in the first sentence, then adds necessary clarification about the measurement scope. It avoids unnecessary fluff and each sentence serves a purpose, though it could be slightly trimmed without losing meaning.

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?

For a read-only tool with a well-defined purpose, documented parameters, and an existing output schema, the description is complete. It explains the ranking and per-region counts, defines the key term 'invisible', and clarifies the corpus limitation. An agent has everything needed to call it correctly and interpret the 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?

Both parameters (days and limit) are fully described in the input schema, including defaults and ranges, so the schema does the heavy lifting. The description does not add extra parameter detail beyond what the schema provides, so the baseline of 3 is appropriate.

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 states a specific verb and resource ('Coverage blind spots') and explains exactly what it returns: companies, models, and people covered by regional press but not Western feeds, ranked with per-region counts. It also provides a clear framing question ('what is Western tech media missing right now?') that distinguishes it from sibling tools like get_region_signal or get_china_signal, which focus on specific regions rather than cross-region gaps.

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 gives useful context by defining 'invisible' within Horizon's corpus and clarifying the measurement scope, but it does not explicitly mention alternatives or state when not to use this tool. It implies a use case (identifying cross-region coverage gaps) but does not compare against siblings like get_region_signal or search_news, so the agent must infer the appropriate choice.

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