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

The description discloses fallback behavior (GDELT preferred, GNews when rate-limited or 5xx), USPTO soft-fail due to API sunset, and the response shape (structured changes[] grouped by source, total_changes count, and pipeworx:// citation URIs). This goes well beyond the readOnlyHint and idempotentHint annotations, giving the agent a clear understanding of what happens during execution.

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 paragraph that front-loads the core purpose and includes essential details like source fallbacks and date formats. Every sentence earns its place, though bullet points for sources and parameters could improve scannability. It is effective but slightly unstructured.

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?

Despite no output schema, the description explicitly explains what is returned (changes[] grouped by source, total_changes count, citation URIs) and covers important edge cases (API sunset, fallback behavior). It also provides a pointer to the sibling tool entity_profile for static profile needs, making the context complete for an agent to choose correctly.

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 covers all three parameters with descriptions, so the baseline is 3. The description adds extra context by linking `since` to the query phrasing ('last N days/weeks/months') and providing examples for `value` (ticker or CIK), though it mostly reinforces schema information. This adds marginal but useful value.

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 over a time window, specifying the sources (SEC, GDELT/GNews, USPTO) and the output format. It also distinguishes itself from entity_profile with an explicit 'Use entity_profile instead' guidance, 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 explicitly tells when to use this tool (e.g., for 'what's new with X' or 'latest on Y' queries within a time window) and provides a clear alternative for static profiles. It also advises a typical monitoring window ('Use '30d' or '1m' for typical monitoring'), which is practical usage guidance.

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