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

With no annotations, the description carries full burden. It discloses that criteria are in percent (5=5%) but outputs are fractional (0.05=5%), which is critical for correct usage. It also notes the cost. However, it does not mention rate limits, result ordering, or behavior when no matches occur.

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?

Two sentences that immediately convey purpose, return fields, and a key format nuance. Every sentence adds value; no wasted words. Front-loaded with the essential action.

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?

For a tool with 9 parameters and no output schema, the description covers the scanning scope (US stocks), criteria types, returned fields, and input/output format. It mentions cost. Missing details like default limit (50) are not stated, but overall it is sufficiently complete for agent decision-making.

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 each parameter described. The description adds a note about percent/fractional conversion, which applies globally but does not significantly enhance individual parameter understanding beyond the schema's existing descriptions.

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 it scans all US stocks on a given date for custom criteria (gaps, volume, change) and lists the returned metrics. This is specific verb+resource+scope, differentiating it from siblings like get_bars (raw data) or list_tickers (symbols only).

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?

No explicit guidance on when to use this tool versus alternatives. It mentions cost ($0.10 USDC) as a practical note, but does not specify when not to scan or compare with related tools like get_bars or query_daily.

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