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

Annotations already establish readOnly/idempotent behavior, but the description adds substantial context: parallel fan-out, source-specific behavior (SEC, GDELT/GNews priority, USPTO soft-fail due to API sunset), and return structure. 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 dense but well-organized, starting with example use cases and then explaining mechanics. Every sentence adds value, though it could be tightened slightly without losing information.

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, time handling, return format), the description covers all key aspects: what it returns, how to specify time, source behavior, and when to use an alternative. No output schema exists, but return structure is described sufficiently.

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 all parameters with descriptions, so baseline is high. The description adds practical nuance for since (ISO vs relative shorthand, examples, typical monitoring recommendation) and clarifies value can be ticker or CIK. This goes beyond 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 clearly defines the tool as a change feed for a company over a time window, fanning out to SEC, news, and patent sources. It uses specific verbs and resources and explicitly differentiates from the sibling tool entity_profile by contrasting windowed changes vs static profiles.

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 concrete example queries that indicate when to use it, and explicitly directs users to entity_profile for static profile needs. It also explains fallback behavior (GDELT→GNews) and gives parameter guidance like '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.