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

Annotations declare readOnlyHint=true, idempotentHint=true, openWorldHint=true, and destructiveHint=false. The description adds substantial context: it fans out to multiple sources (SEC EDGAR, GDELT/GNews fallback, USPTO), notes API sunset and soft-fail behavior, and describes the return format. No contradictions with 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 a single paragraph but is dense with useful information. It front-loads example queries and uses clear language. While slightly compact, every sentence contributes meaning. Could be slightly more structured (e.g., bullet points) but remains highly efficient.

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?

There is no output schema, but the description outlines return fields ('structured changes[] grouped by source + total_changes count + pipeworx:// citation URIs'), which is sufficient. All aspects of the tool—parameters, behavior, fallbacks, and exclusions—are covered. The tool's simplicity and rich annotations make this complete.

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% with descriptions for all three required parameters. The description adds value by explaining the `since` parameter's accepted formats (ISO date or relative shorthand) with an example usage hint ('Use "30d" or "1m" for typical monitoring'), and clarifies that `value` accepts ticker or CIK. This goes 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 returns a change feed for a company over a recent time window, with example queries like 'What's new with X'. It explicitly distinguishes from sibling tool 'entity_profile' by specifying when to use the alternative. The verb 'return' and resource 'change feed' are specific and 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?

The description provides explicit guidance on when to use this tool (e.g., 'What's new with X', 'latest on Y') and when not to ('Use entity_profile instead when you want the static profile...'). It also explains fallback behavior between GDELT and GNews, giving clear context for invocation.

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