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

Annotations already mark this as read-only, open-world, and idempotent, but the description adds substantial context: it fans out to SEC EDGAR, GDELT→GNews (with GDELT preferred and GNews as fallback on rate limit/5xx), and USPTO (with PatentsView API sunset May 2025 causing a soft-fail). It also states the parallel call behavior and the return structure. No contradictions.

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?

Despite its length, every sentence earns its place: examples, source list with fallbacks, parameter shorthand, return structure, and alternative tool guidance. The description is front-loaded with example queries and remains dense without redundancy.

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?

The tool has no output schema, but the description explains what the return looks like (structured changes[] grouped by source, total_changes count, and citation URIs). It also covers edge cases like the USPTO soft-fail and gives usage guidance for `since`. This is complete for a tool of this complexity.

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?

Input schema provides 100% coverage with descriptions for all three parameters, including enums and examples. The description repeats the `since` shorthand examples but adds no new parameter-level information; it does add context about the parallel fan-out, but that's not parameter-specific. Therefore baseline 3 is appropriate.

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 queries like "What's new with X" and explicitly states it's a "change feed for a company in the last N days/weeks/months in ONE parallel call," naming three data sources and the structured output. It clearly distinguishes from sibling entity_profile by contrasting the change feed vs static profile.

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 explicitly tells the agent when to use this tool vs entity_profile: 'Use entity_profile instead when you want the static profile... regardless of window.' It also provides typical `since` values ('Use "30d" or "1m" for typical monitoring') and notes fallback behavior and soft-fails, giving clear context for when this tool is appropriate.

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