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

Annotations already declare readOnlyHint/idempotentHint/destructiveHint, and the description adds important behavioral details: parallel fan-out to multiple APIs, GDELT-to-GNews fallback on rate limits/5xx, and USPTO soft-fail due to PatentsView sunset. It does not exhaustively cover error handling or ordering, but the additional context is valuable and non-contradictory.

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, leading with user-friendly examples and then explaining sources, parameter formats, return value, and alternatives. Every sentence adds information, though the length is substantial for a tool with only three parameters; it earns its length by covering multi-source complexity.

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?

With no output schema, the description compensates by clearly stating the return structure ('structured changes[] grouped by source + total_changes count + pipeworx:// citation URIs'). It also covers parameter formats, source fallbacks, and an alternative tool, making it sufficiently complete for a read-only aggregator. Minor gaps like empty-result behavior or timeout handling are not critical given the transparency provided.

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%, providing baseline descriptions for all three parameters. The description enriches semantics with concrete examples: '7d', '30d', '3m', '1y' for `since`, ticker/CIK formats for `value`, and notes that `type` only supports 'company' today. These examples clarify usage beyond 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 clearly states the tool provides a 'change feed for a company in the last N days/weeks/months' with specific sources (SEC EDGAR, GDELT/GNews, USPTO). It explicitly distinguishes from entity_profile, noting to use that instead for static profiles, which sets it apart from a likely sibling.

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?

It provides natural language triggers ('What's new with X', 'latest on Y') to signal appropriate use, and explicitly directs users to entity_profile when a static profile is needed regardless of window. This gives clear when-to-use and when-not-to-use guidance beyond the schema.

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