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

The description discloses detailed behavioral traits beyond the annotations: it fans out to SEC EDGAR, GDELT with GNews fallback, and USPTO (with soft-fail note). It explains the parallel call nature, the return format, and the citation URIs. No contradiction with annotations (readOnlyHint, idempotentHint, etc.).

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 dense but well-structured: it opens with example queries, then explains the fan-out, parameter specifics, return format, and sibling distinction. Every sentence serves a purpose; however, it is slightly verbose for the 'what's new' examples, which could be condensed. Still, it maintains a logical flow.

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 complexity (multiple data sources, fallback logic, soft-fail, date formats, return structure), the description covers all essential aspects. No output schema exists, but the description explicitly lists the returned fields (changes grouped by source, total_changes, citation URIs), making the tool self-contained for invocation.

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?

Although the schema already has 100% coverage with good descriptions, the tool description adds extra value: it provides typical usage examples for 'since' (e.g., 'Use "30d" or "1m" for typical monitoring') and confirms that 'type' only supports 'company'. The description enhances the semantic understanding beyond the schema alone.

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 is exceptionally clear, starting with example user queries ('What's new with X', 'latest on Y') and then stating the tool's purpose: a change feed for a company in a recent window. It explicitly distinguishes itself from the sibling 'entity_profile' tool by specifying when to use each, providing strong purpose clarity.

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 provides explicit when-to-use guidance with real queries and examples. It also clearly states when not to use this tool: 'Use entity_profile instead when you want the static profile'. This directly helps the agent decide between siblings.

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