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

The description richly discloses behavior beyond the readOnly/idempotent annotations: it fans out to SEC EDGAR, GDELT→GNews with a fallback, and USPTO with a 'soft-fails' note due to PatentsView API sunset. This level of transparency about failure modes and data sources is beyond what annotations provide.

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 well-structured, with a front-loaded intent phrase and methodical breakdown of sources and fallbacks. It could be tightened by trimming some repetitive examples, but it remains readable and informative.

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 complex tool with no output schema, the description explains the return shape (changes[], total_changes, citation URIs) and source-specific failure modes. It also provides an alternative, making it complete for an agent to invoke 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 coverage is 100% and the description does not add much beyond the schema for `value`, `type`, or `since`. It restates the same ISO/relative shorthand for `since` and CIK format for `value`, so the baseline of 3 applies.

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 explicitly defines the tool as a 'change feed for a company' and provides natural language examples that clarify intent. It also distinguishes from entity_profile by explicitly noting when to use that alternative, making the tool's scope 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 gives direct usage guidance: use for 'what's new' queries and explicitly says 'Use entity_profile instead when you want the static profile... regardless of window.' This clearly frames when to select this tool over a sibling.

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