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

Goes well beyond the readOnly/openWorld/idempotent annotations by disclosing fan-out to multiple APIs, GDELT-to-GNews fallback on rate-limit/5xx, USPTO soft-fail due to PatentsView sunset, return shape (changes[] grouped by source, total_changes, citation URIs), and the meaning of 'ONE parallel call'. No contradictions 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?

Dense yet well-organized: begins with user-intent phrasing, then states core function, enumerates sources/fallbacks, parameter semantics, return format, and closes with an alternative—all in four sentences. Every clause earns its place, no filler or repetition.

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 multi-source tool with no output schema, the description fully covers inputs, behavior, source fallbacks, failure modes, return fields, and usage boundaries. It also addresses the sibling entity_profile to prevent misuse. Nothing critical is missing.

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 already covers all three parameters at 100%, so baseline is 3. The description adds value by detailing `since` formats with examples and a practical default ('30d' or '1m'), and explains `value` as ticker or CIK with examples (though the schema already had similar text). This elevates it to a 4.

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 opens with concrete natural-language triggers ("What's new with X" / "latest on Y") and defines the tool as a 'change feed for a company in the last N days/weeks/months'. It explicitly lists the data sources (SEC, GDELT/GNews, USPTO) and contrasts with sibling entity_profile, making the purpose unmistakable and sibling-differentiated.

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?

Provides abundant when-to-use guidance: example queries, window formats (ISO or relative), typical monitoring recommendation ('30d' or '1m'), and an explicit alternative ('Use entity_profile instead when you want the static profile...'). Also explains fallback behavior for rate limits, which helps the agent choose appropriately.

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