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

Annotations already declare readOnly, idempotent, and openWorld hints, but the description goes far beyond them: it details fan-out to SEC EDGAR, GDELT→GNews fallback on rate limits/5xx, USPTO sunset soft-fail, and the structured return format with citation URIs. This is rich behavioral context not inferable from 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 well-structured and front-loaded with examples, then explains mechanisms, parameter details, return shape, and the alternative tool. Every sentence provides useful information without redundancy or fluff.

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 adequately explains the return value (changes[] grouped by source, total_changes, citation URIs) and source fallbacks. It could optionally mention potential limitations like result caps or error handling, but the key aspects are covered. The distinction from entity_profile closes the loop.

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 description only restates the `since` parameter format already present in the schema (ISO date or relative shorthand). It does not add new semantic meaning for parameters; the baseline of 3 applies.

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 begins with concrete example queries and states the core function: 'change feed for a company in the last N days/weeks/months in ONE parallel call.' It also explicitly distinguishes from the sibling tool entity_profile, making the purpose unambiguous.

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 clear when-to-use guidance via example queries and explicitly says 'Use entity_profile instead when you want the static profile.' Additionally, it explains fallback behavior (GDELT preferred, GNews when rate-limited) and source behavior (USPTO soft-fails), giving the agent context on when to rely on this tool.

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