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

No annotations, so description must disclose behavior. It notes 'PRO' (subscriber token required) and scope (liquid perps), but omits whether it's read-only, rate limits, return format, and pagination. Minimal behavioral context.

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?

Short and front-loaded, with 'PRO.' flagging the tier. However, the sentence could be slightly clearer about what the tool returns (e.g., 'Returns...'). It's efficient but not perfectly structured.

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 data retrieval tool with no output schema and no annotations, the description should explain parameters and output fields. It mentions annualised APR but leaves n and min_volume_usd undefined, making it incomplete for correct invocation.

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?

Only access_token is described in schema; n and min_volume_usd lack descriptions. The description doesn't explain what n controls or how min_volume_usd filters, leaving two of three parameters ambiguous despite low schema coverage.

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 specifies the resource (funding rates) and scope (liquid perps) and indicates the output (most positive/negative, annualised APR). It distinguishes from siblings by focusing on extremes (crowded longs/shorts), though it doesn't explicitly name alternatives.

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?

Implies usage for identifying crowded longs/shorts, but gives no explicit when-to-use or when-not, nor does it reference siblings like perp_scanner. A user must infer from 'crowded longs/shorts' that it's for sentiment analysis.

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