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

No annotations are provided, so the description carries the full burden. It discloses key behavioral aspects: the audit is public, samples every 10 minutes, and includes metrics like diff %, snapshot age, and 24h mean/max. It also implies a read-only nature and warns about trust implications, though it does not explicitly state side-effect-free behavior.

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 reasonably concise and front-loaded with the core purpose ('public accuracy audit'). Each sentence adds value, though the final warning is more advisory than informational. Slightly longer than strictly necessary but well organized.

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?

With no output schema, the description must summarize return values, and it does: diff %, snapshot age, 24h mean/max, and liquidation map scoring. It does not detail the exact response structure, but for a no-parameter, read-only audit tool, this is adequate for an agent to know what data it will receive.

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 tool has zero parameters)Skip; the schema is emptyholonomic. With no parameters to document, the description already provides sufficient information about what the tool returns. Baseline 4 applies.

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 function: it provides a public accuracy audit comparing open interest and funding against external exchange endpoints, and also scores the modeled liquidation map. This is specific and distinguishes it from sibling tools that report raw data (e.g., get_open_interest, get_funding_rates) rather than data quality metrics.

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 advises 'Read this before trusting any number here with money,' which tells the agent when to use this tool: when evaluating the reliability of other data. It does not name alternatives, but there are no sibling accuracy tools, so the usage context is clear enough.

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