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

The description goes well beyond the annotations by disclosing the fan-out to SEC EDGAR, GDELT→GNews fallback, USPTO's soft-fail due to PatentsView sunset, and the exact meaning of the 'since' parameter. It also describes the return structure, which is essential since no output schema is provided. 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 front-loaded with use-case phrases, then systematically covers data sources, fallback behavior, date formats, output shape, and alternative tools. Every sentence adds information; there is no fluff or redundancy despite the length.

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 tool with no output schema, the description fully explains what the tool returns (changes[] grouped by source, total_changes, citation URIs) and covers edge behavior (rate limits, API sunset, soft-fail). It also names the primary alternative, making the tool's scope complete 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 coverage is 100%, so baseline is 3. The description repeats the parameter semantics (ISO date vs. relative shorthand, ticker or CIK) already present in the schema, but adds no genuinely new param-level meaning beyond reinforcing examples already in 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 in the last N days/weeks/months' and enumerates the natural language triggers it serves. It also explicitly distinguishes itself from entity_profile, making its purpose unambiguous and differentiating it from a key sibling.

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?

It provides explicit usage cues ('What's new with X', 'latest on Y') and states when to use entity_profile instead ('when you want the static profile ... regardless of window'). It also explains the tool's parallel fan-out and fallback behavior, giving clear context for choosing it over alternatives.

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