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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds valuable behavioral context: it fans out to SEC EDGAR, GDELT→GNews with fallback, and USPTO with soft-fail due to PatentsView API sunset. It also discloses the return structure (changes[] grouped by source + total_changes count + citation URIs). 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?

The description is information-dense but well-structured. It leads with relatable query examples, then explains the data sources, fallback behavior, date format, return shape, and alternatives in a single flowing passage. Every sentence contributes meaningful detail; there is no filler.

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 data sources, fallback logic, soft-fail mode, and no output schema—the description covers all critical aspects: sources, failure modes, return structure, and the alternative tool. It even notes the single parallel call efficiency. No important gap is evident.

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 100% coverage of all three parameters. The description adds practical value by explaining the 'since' format: ISO date or relative shorthand ('7d', '30d', '3m', '1y'), and recommending '30d' or '1m' for typical monitoring. This goes beyond the baseline schema description.

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 user query examples and defines the tool as a 'change feed for a company in the last N days/weeks/months in ONE parallel call.' It explicitly distinguishes itself from entity_profile, stating that recent_changes is for time-windowed changes, while entity_profile covers static profiles. This is a specific verb+resource description that fully clarifies purpose.

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 clear when-to-use signals: examples of user intents ('What's new with X', 'latest on Y') and explicit alternative guidance: 'Use entity_profile instead when you want the static profile ... regardless of window.' It also explains the fallback logic (GDELT preferred, GNews when rate-limited or 5xx), helping 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.