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

The description goes well beyond the readOnly/idempotent annotations by disclosing the multi-source fan-out behavior, the GDELT→GNews fallback chain, the USPTO soft-failure due to PatentsView API sunset, and the exact return shape (changes[], total_changes, citation URIs). This provides rich behavioral context without contradicting 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 long but front-loaded with user-facing query examples and structured logically: use case, fan-out behavior, parameter formats, return shape, and alternative tool. Every clause contributes meaningful detail, though some implementation specifics could be trimmed without losing 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?

With no output schema, the description fully explains what the tool returns, including grouped changes, total count, and citation URIs. It also covers failure modes and source selection logic, making it complete for a complex multi-source tool.

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%, so the baseline is 3, but the description adds a practical usage recommendation ('Use "30d" or "1m" for typical monitoring') and reinforces the accepted formats with concrete examples. It doesn't fundamentally change parameter understanding but does add minor guidance 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 explicitly states it provides a 'change feed for a company in the last N days/weeks/months' and enumerates concrete query patterns like "What's new with X" and "latest on Y". It also distinguishes itself from the sibling tool entity_profile by explicitly recommending that tool for static profiles.

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 clear when-to-use guidance through example natural-language queries and a recommended time window. It explicitly names an alternative (entity_profile) and explains when to use it instead, satisfying the when-not and alternatives criteria.

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