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

Beyond the annotations (readOnly, openWorld, idempotent), the description discloses critical behavioral traits: it fans out to multiple sources in parallel, documents a fallback chain (GDELT→GNews), and reveals a known soft-fail for USPTO due to API sunset in May 2025. It also states the return structure (changes[], total_changes, citation URIs). This is rich, honest behavioral context.

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 dense but every sentence adds value: examples, core definition, data source breakdown, fallback logic, parameter details, return format, and an explicit alternative. It is front-loaded with the core purpose and avoids fluff, making it highly efficient for an agent to parse.

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, fallbacks, no output schema), the description is exceptionally complete. It covers the return shape (changes[], total_changes, citation URIs), the behavior of the `since` parameter, source-specific behavior including a known failure mode, and references an alternative tool. No critical aspects are left unexplained.

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 full descriptions for all three parameters (type, since, value), including accepted formats and examples. The tool description adds little beyond restating the `since` format and giving usage context. With 100% schema coverage, the baseline score of 3 is appropriate; the description does not substantially exceed what the schema offers.

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 clearly defines the tool as a change feed for a company over a recent window, with example query patterns and explicit source details (SEC EDGAR, GDELT/GNews, USPTO). It distinguishes itself from the sibling tool entity_profile by stating when to use each. This is a specific, well-scoped purpose statement.

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 when-to-use guidance through natural language examples and clarifies when NOT to use it: 'Use entity_profile instead when you want the static profile (filings + fundamentals + LEI + patents) regardless of window.' It also specifies preferred usage of the `since` parameter ('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.