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

Beyond the annotations (readOnlyHint, idempotentHint, etc.), the description details fan-out behavior, source fallbacks, the PatentsView sunset soft-fail, accepted date formats, and return shape (changes[], total_changes, pipeworx:// URIs). This gives the agent a robust model of what will happen when the tool is invoked.

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 information-dense but well-organized, with a front-loaded intent list followed by source details, input formats, output summary, and alternative tool guidance. It could be slightly trimmed (e.g., multiple example queries), but every sentence contributes useful decision-making or behavioral 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 no output schema, the description adequately explains the return structure and data provenance. It covers input flexibility, fallback behavior, failure modes, and explicitly tells the agent when to use a different tool. This is complete for a multi-source, moderate-complexity tool.

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?

The schema already covers all parameters (100%), but the description adds practical guidance on `since` formats and recommends '30d' or '1m' for typical monitoring. It reinforces the zero-padded CIK/ticker semantics. This goes slightly beyond the schema, though most parameter detail is already present.

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 identifies the tool as a change feed for a company over a configurable window, with concrete natural-language triggers ('What's new with X', 'updates on Acme'). It names the underlying data sources (SEC EDGAR, news, patents) and explicitly contrasts with entity_profile, making it easy to distinguish from siblings.

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 provides explicit when-to-use guidance: it targets recent-change queries over a window, and says to use entity_profile instead when a static profile is needed regardless of window. It also explains internal fallback behavior (GDELT→GNews) and the USPTO soft-fail, which helps the agent decide when this tool is appropriate.

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