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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false. The description adds meaningful behavioral context: parallel calls to multiple sources, fallback logic, soft-fail for patents, and the return shape (changes[] grouped by source, total_changes, pipeworx:// URIs). No contradiction 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 compact and front-loaded with practical examples. Each sentence earns its place, though it could be slightly trimmed without losing clarity. The structure effectively guides understanding from purpose to nuance.

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 3-required-parameter tool with no output schema, the description sufficiently explains the return structure (changes[] grouped by source, total_changes, citation URIs) and edge cases (patents soft-fail, news fallback). An agent can fully understand inputs and outputs.

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%, so the schema already documents all params. The description adds value by providing usage examples for since (ISO date, relative shorthand, and recommended '30d' or '1m') and value (ticker, CIK with examples). This extra context aids correct invocation.

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 example queries ('What's new with X', 'latest on Y') and explicitly states 'change feed for a company in the last N days/weeks/months in ONE parallel call.' It clearly distinguishes from sibling entity_profile by directing when to use that alternative.

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: 'Use entity_profile instead when you want the static profile... regardless of window.' It also details fallback behavior (GDELT→GNews) and soft-fail conditions for patents, giving clear when-to-use and when-not-to-use context.

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