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

Annotations already mark the tool as read-only, idempotent, and non-destructive. The description adds rich behavioral detail not present in the annotations: the fan-out to SEC EDGAR, GDELT→GNews fallback, USPTO soft-fail due to API sunset, and the returned citation URIs. It also signals rate-limit/failure behavior.

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 a dense, single block of text, but every piece earns its place: use cases, source fan-out, fallback behavior, parameter expectations, and return summary. It is front-loaded with the user-intent phrases, though it could be slightly better structured with more whitespace or bullets.

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?

Even without an output schema, the description explains the return shape (structured changes[] grouped by source, total_changes count, pipeworx:// citation URIs), the data sources, and failure modes. This is a complete picture for a complex tool with no output schema.

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%, so the baseline is 3. The description repeats the `since` format and provides examples ('7d', '30d') already present in the schema, and clarifies `value` accepts ticker or CIK — but these are already documented. It adds no substantial new parameter semantics 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 identifies the tool as a change feed for a company over a time window, with explicit user-facing phrasings ('What's new with X', 'updates on Acme'). It distinguishes itself from the sibling entity_profile by contrasting the change feed with the static profile tool.

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 gives concrete example queries and states the exact alternative: 'Use entity_profile instead when you want the static profile... regardless of window.' This provides a clear when-to-use and when-not-to-use directive, plus context on the parallel fan-out behavior.

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