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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds significant behavioral details: it fans out to multiple sources (SEC, GDELT→GNews, USPTO), explains the fallback mechanism (GDELT preferred, GNews when rate-limited or 5xx), notes USPTO soft-failing due to API sunset, and outlines 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 a single, dense paragraph that front-loads examples, clearly states the tool's purpose, explains the underlying mechanics, and ends with an explicit alternative. Every sentence contributes value with no wasted words.

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 moderate complexity (multiple data sources, fallback behavior, failure conditions) and the absence of an output schema, the description provides sufficient context: it describes the return format (changes grouped by source, count, URIs), handles edge cases (soft-fails, rate limits), and gives a complete picture of what the tool does and returns. The annotations already guarantee safety and idempotency, so no further behavioral assurances are needed.

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?

Schema coverage is 100% with descriptions for all three parameters. The description adds value beyond the schema by clarifying 'since' format details (ISO date or relative shorthand, suggesting '30d' or '1m' for monitoring), explaining that 'type' currently only supports 'company', and giving examples for 'value' (ticker or zero-padded CIK). This enriches the schema information without redundancy.

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 starts with multiple concrete query examples and explicitly states it is a 'change feed for a company in the last N days/weeks/months in ONE parallel call.' It lists the data sources (SEC EDGAR, GDELT→GNews, USPTO) and distinguishes itself from the sibling entity_profile tool by describing what it does that the sibling does not.

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 includes an explicit alternative: 'Use entity_profile instead when you want the static profile ... regardless of window.' It also provides typical query examples and suggests using '30d' or '1m' for typical monitoring, giving clear direction on when and where 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.