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

Beyond the annotations (read-only, idempotent), the description discloses the fan-out architecture, the GDELT→GNews fallback on rate-limit/5xx, the USPTO PatentsView API sunset causing a soft-fail, and the exact return structure. This is rich behavioral context.

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 long but each sentence adds essential information. It front-loads user-facing query phrasings, then details sources, fallback behavior, and return format. No fluff, but it is dense enough that a slightly more compact structure could improve skimmability.

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's complexity and absence of an output schema, the description fully covers what the tool does, when to use it, how fallback works, input date formats, return shape, and the key alternative tool. There is no significant gap in contextual information.

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?

The input schema already covers all three parameters with 100% description coverage. The description adds extra meaning by explaining `since` accepts ISO date or relative shorthand with examples ('7d', '30d', '3m', '1y') and recommends '30d' or '1m' for typical monitoring, going beyond the schema.

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 clearly states this is a change feed for a company over a time window, with concrete query examples like 'what's new with X'. It explicitly distinguishes itself from sibling entity_profile by naming the alternative and its different use case.

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 provides explicit when-to-use phrasing ('What's new with X', 'latest on Y') and tells the agent to use entity_profile instead when a static profile is needed 'regardless of window'. This is an explicit alternative and exclusion.

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