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

Annotations already indicate read-only, idempotent behavior. The description adds valuable behavioral detail: fan-out to three sources, GDELT→GNews fallback, USPTO soft-fail, and return structure (grouped changes, count, 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 a single paragraph but logically organized: examples, core function, sources, input details, output overview, and alternative tool. Every sentence adds value. Slightly verbose for the high density of information, but adequately concise overall.

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 sources, fallback, relative dates, return format) and the absence of an output schema, the description covers the key aspects. It explains what the tool returns and what it does not do (static profile). Minor gaps: no example output structure, but sufficient for agent selection.

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?

With 100% schema coverage, baseline is 3. The description adds significant context: examples of relative shorthand for 'since' ('7d', '30d'), recommendation of '30d' or '1m', explanation of 'value' accepting ticker or CIK, and noting that 'type' currently only supports 'company'. This improves usability.

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 the tool's function: a parallel change feed for a company, aggregating SEC filings, news, and patents. It distinguishes itself from sibling tool entity_profile by specifying when to use each. Examples of user queries make the purpose intuitive.

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 explicitly contrasts with entity_profile, guiding when to use this tool for change feed vs. static profile. It also implies efficiency with 'ONE parallel call.' However, it does not address other potential competitors like compare_entities, though the focus on temporal changes narrows usage well.

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