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

Annotations already indicate read-only, open-world, idempotent, non-destructive behavior. The description adds significant behavioral detail: data source fan-out (SEC EDGAR, GDELT→GNews fallback, USPTO), specific fallback triggers (rate-limited or 5xx), and the PatentsView sunset condition causing soft-fail. This goes well beyond the 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 longer than average, but every sentence contributes essential operational detail (sources, fallbacks, parameter syntax, return structure, alternative tool). It is front-loaded with the most common use cases. Slightly dense, but not wasteful.

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 complex, multi-source aggregation tool with no output schema, the description is thorough: it explains return shape (changes[] grouped by source, total_changes count, pipeworx:// citation URIs), fallback behavior, parameter formats, and the appropriate alternative tool. No critical gaps for an agent to invoke it 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?

Schema covers 100% of parameters, but the description adds meaningful semantics: `since` formats (ISO date vs relative shorthand like '7d', '30d', '3m', '1y'), `value` examples (ticker vs zero-padded CIK), and `type` restriction to 'company'. This adds value beyond the schema definitions.

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 intents ('What's new with X' / 'latest on Y') and clearly states this is a change feed for a company over a time window, aggregating multiple sources in one parallel call. It also distinguishes itself from entity_profile, making the purpose unmistakable.

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 explicit guidance on when to use this tool vs. the sibling entity_profile tool: 'Use entity_profile instead when you want the static profile... regardless of window.' Also clarifies supported entity type (company only) and gives typical usage examples (e.g., 'Use "30d" or "1m" for typical monitoring').

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