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

Beyond the readOnly/idempotent annotations, the description reveals detailed internal behavior: it fans out to SEC EDGAR, GDELT→GNews fallback, and USPTO (with a soft-fail note about the PatentsView API sunset). It specifies the fallback logic (GDELT preferred, GNews on rate-limit/5xx) and the return structure, which is far more than annotations alone provide.

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 front-loaded with intuitive examples, then provides a concise definition, source details, return format, and alternative tool reference. Every sentence contributes new information without redundancy, making it efficient despite its length.

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?

Since there is no output schema, the description fully explains the return value (structured changes[] grouped by source, total_changes count, citation URIs). It also covers edge cases like the USPTO soft-fail and fallback logic, ensuring the agent understands the tool's behavior in all circumstances.

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 with high coverage (100%), so the baseline is 3. The description adds value by clarifying accepted formats for `since` with examples ('7d', '30d', '3m', '1y') and recommending '30d' or '1m' for typical monitoring, which goes beyond the schema description.

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 a specified time window, with examples of natural language queries that map to it. It explicitly distinguishes itself from the sibling tool entity_profile, which provides static profiles.

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 usage context through example queries like 'What's new with X' and directly names an alternative tool ('Use entity_profile instead') for static profiles. It also explains the source fan-out and fallback behavior, making it clear when to invoke this tool.

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