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

The description adds significant behavioral context beyond the annotations: fan-out to SEC EDGAR, GDELT→GNews fallback, USPTO soft-fail, accepted date formats, and return structure (changes grouped by source, total_changes, citation URIs). There is 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 relatively compact given the complexity, with front-loaded example queries. Every sentence adds useful information, though it could be slightly trimmed without losing critical details. The structure is clear and logical.

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 tool with no output schema, the description thoroughly explains the return structure (changes[], total_changes, citation URIs) and covers all key aspects: data sources, fallback behavior, date formats, and parameter nuances. It is complete enough for an agent to use effectively.

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% with parameter descriptions. The description adds value by providing concrete examples (e.g., 'use "30d" or "1m"'), clarifying that value can be ticker or CIK, and explaining the type parameter's current limitation (only 'company' supported). This goes beyond simply restating the schema.

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 starts with clear example queries and explicitly states it provides a change feed for a company within a date window, fanning out to multiple sources. It also distinguishes itself from the sibling tool entity_profile, which serves a different purpose (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 includes example queries, specifies parameter usage (e.g., 'use "30d" or "1m" for typical monitoring'), and explicitly tells when to use entity_profile instead ('when you want the static profile... regardless of window'). This provides clear usage guidance and alternatives.

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