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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, but the description adds substantial behavioral context beyond that: fan-out to multiple APIs, GDELT→GNews fallback behavior ('GDELT preferred, GNews when rate-limited or 5xx'), the USPTO PatentsView sunset limitation, accepted date formats, and the return structure (changes[] with total_changes and citation URIs). This is rich disclosure with 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 long but information-dense and well-structured: it front-loads the purpose with example queries, then covers sources, fallback logic, parameter syntax, return summary, and alternative tool in a logical order. Every sentence carries necessary detail, and there is no padding or tautology.

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?

This is a complex multi-source fan-out tool with no output schema, yet the description covers all essential operational aspects: input parameter formats, source behaviors, fallback conditions, known limitations (PatentsView sunset), output composition, and alternative tool linkage. An agent has sufficient information to select and invoke it correctly in a variety of user intents.

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 description coverage is 100%, and the schema already documents each parameter well ('since' explains ISO/relative formats, 'value' explains ticker/CIK, 'type' explains only company supported). The description adds slight context by explaining how 'since' is used in the fan-out ('filings since `since`') and giving natural-language examples, but it mostly duplicates schema info. 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 example queries and then states 'change feed for a company in the last N days/weeks/months in ONE parallel call', clearly specifying the verb (provide change feed) and resource (company). It lists the data sources (SEC EDGAR, GDELT→GNews, USPTO) and explicitly distinguishes from sibling entity_profile ('Use entity_profile instead when you want the static profile'), so it scores 5.

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 gives explicit when-to-use context: 'change feed for a company in the last N days/weeks/months', and provides a clear alternative: 'Use entity_profile instead when you want the static profile (filings + fundamentals + LEI + patents) regardless of window.' This directly tells the agent when not to use this tool and points to a specific sibling, satisfying the top criterion.

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