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

Annotations already declare readOnly, openWorld, idempotent, and non-destructive, so the bar is lower. The description adds valuable behavioral context: concurrent fan-out to multiple sources, GDELT-to-GNews fallback on rate limits or 5xx, and USPTO's soft-fail due to API sunset. However, it doesn't disclose authentication requirements or error handling beyond the fallback, so a 4 is appropriate.

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 dense paragraph but is well-structured with examples, source details, parameter syntax, and output summary. It earns its length given the tool's complexity, but could be broken into bullet points for readability. No filler sentences.

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 explains the return structure (changes[] grouped by source, total_changes count, citation URIs). It covers all parameters, sources, fallback behavior, and alternative tools. For a tool with this complexity, the description is highly 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%, so baseline is 3. The description adds extra meaning for 'since' by specifying allowed formats ('ISO date or relative shorthand') and recommending '30d' or '1m' for typical monitoring. It also reinforces 'value' accepting ticker or CIK. This goes slightly beyond the schema, justifying a 4.

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's purpose: a change feed for a company over the last N days/weeks/months, with example queries like 'What's new with X' and 'latest on Y'. It also distinguishes itself from entity_profile, which is for static profiles, making the purpose unambiguous and distinct 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?

It provides explicit when-to-use guidance with example natural language queries, and explicitly says 'Use entity_profile instead when you want the static profile', giving a clear alternative. It also explains the internal fan-out to SEC EDGAR, GDELT/GNews, and USPTO, which helps the agent decide based on data needs.

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