Derivatives pressure scores (funding + OI + basis composite)

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

The description discloses the scoring methodology (funding rate, 1h/4h/24h OI deltas, basis) and output fields (direction, regime label), which goes beyond the readOnlyHint=true and openWorldHint=true annotations. This doesn't contradict the annotations (which indicate a safe, read-only, open-world operation) and adds useful behavioral context about how the score is computed.

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 exactly two sentences, with the use case front-loaded first, the alternative tool second, and the output composition in the same first sentence. Every phrase contributes to understanding when and how to use the tool, with no filler or repetition.

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 the tool has no output schema, the description does well to explain the nature of the result (composite 0-100 score, direction, regime label). It also mentions symbol filtering and ranking. While it doesn't spell out default limits or pagination, those are covered in the parameter schema, so the description is complete enough for a straightforward read-only query tool.

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 input schema already provides clear descriptions for both parameters (limit and symbol), so the description adds no extra semantic detail. However, it does implicitly reference the 'symbol' parameter ('specific coins') and the 'limit' parameter ('top-10 ranking'), reinforcing their usage. Since schema coverage is 100%, the baseline of 3 is appropriate.

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: it returns crowded/over-leveraged coins or a derivatives-stress score for specific coins. It also describes the output components (0-100 composite score, direction, regime label), making the tool's function unambiguous. It distinguishes itself from the sibling get_top_movers by naming that tool as an alternative for a different use case.

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 explicitly states when to use this tool: 'when the user asks which coins are crowded or over-leveraged, or asks for the pressure/derivatives-stress score of specific coins.' It also gives an explicit exclusion: for a quick top-10 ranking, 'use get_top_movers instead.' This is clear, actionable guidance for an AI agent to select between tools.

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