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

Beyond the annotations (readOnly, openWorld, idempotent), the description details the data sources (SEC EDGAR, GDELT→GNews fallback, USPTO), the fallback mechanism, and the PatentsView sunset soft-fail. It also discloses the return structure (changes[] grouped by source, total_changes, citation URIs). This is rich behavioral context.

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 compact yet dense, front-loaded with query examples, then source mechanics, parameter syntax, and return format. Every clause adds value, and the alternative tool mention is placed at the end for emphasis.

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 read-only feed tool with no output schema, the description covers usage, sources, fallback behavior, parameter syntax, return structure, and an alternative. It is sufficiently complete for an agent to invoke correctly without additional context.

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?

The schema already covers all parameters fully, but the description adds practical semantics: 'since' accepts ISO dates or relative shorthand with examples, and 'value' is exemplified with a ticker and CIK. It also notes 'type' only supports 'company' today.

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 identifies the tool as a change feed for a company over a date window, with specific verbs like "what's new" and "updates on". It distinguishes from sibling tool entity_profile by explicitly noting 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?

Provides explicit example queries ('What's new with X', 'updates on Acme') and a clear alternative rule: 'Use entity_profile instead when you want the static profile...'. This gives the agent concrete guidance on when to choose 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.