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

Annotations already declare safe read-only, idempotent behavior. The description adds significant behavioral details: fans out to multiple sources in parallel, fallback from GDELT to GNews, soft-fail for USPTO patents, and return structure including citation URIs. 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 relatively long but front-loaded with common use cases. It packs a lot of necessary information into a few sentences. While it could be slightly tighter, it avoids redundancy and each sentence adds value.

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 (multiple data sources, parameter options, fallback behavior) and the absence of an output schema, the description covers all critical aspects: sources, date handling, return format, and alternative tool. It is complete enough for an agent to use correctly.

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 baseline is 3. The description adds value beyond schema by explaining the 'since' parameter accepts both ISO dates and relative shorthand with examples ('7d', '30d', '3m', '1y'), and recommends '30d' or '1m' for typical monitoring. It also clarifies that 'value' can be a ticker or zero-padded CIK.

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 starts with representative queries and states the tool provides a change feed for a company, covering SEC, news, and patents. It explicitly distinguishes itself from the sibling tool entity_profile, which focuses on static profiles. The verb 'change feed' and resource 'company' are specific and clear.

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 scenarios ('What's new with X', 'latest on Y') and when-not-to-use (use entity_profile instead for static profile). It also gives alternatives and usage context, such as the fallback behavior between GDELT and GNews.

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