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

The description goes beyond the readOnly/openWorld/idempotent annotations by disclosing the specific external APIs (SEC EDGAR, GDELT→GNews fallback, USPTO) and their failure modes (GNews when rate-limited, USPTO soft-fail after May 2025). It also specifies the return structure, including grouped changes and citation URIs, which is valuable 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 front-loaded with example queries and a clear statement of scope, then efficiently details fan-out sources, parameter syntax, return structure, and alternatives in about 110 words. Every sentence provides useful information without redundancy, making it appropriately dense for the tool's complexity.

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?

Despite lacking an output schema, the description explains the return format (changes[] grouped by source, total_changes count, citation URIs) and covers external dependencies and fallback behavior. It could mention edge cases like empty results or rate limits on the tool itself, but overall it gives an agent sufficient context to select and invoke the tool 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?

The input schema already provides comprehensive descriptions for all three parameters (type enum, since format, value formats), covering 100% of the schema. The description reinforces these with examples and suggests '30d' or '1m' for typical monitoring, but does not add substantive semantic meaning beyond 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 defines the tool as a change feed for a company over a specified window, listing concrete query examples and the sources it fans out to. It explicitly distinguishes itself from entity_profile, which provides static profiles, making its scope immediately clear.

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 usage guidance by listing natural-language triggers ('What's new with X') and stating it handles the last N days/weeks/months in one parallel call. It also gives an explicit alternative: use entity_profile for static profiles, clarifying when not to use this tool.

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