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

Annotations already declare this a safe, read-only, idempotent operation, but the description adds real behavioral detail: the 0.5% threshold, pre-ranking, and that unit-mismatch outliers (>400 bps from median, e.g. 1000SHIB) are filtered out. Minor gaps remain around row limits or pagination for the full matrix.

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?

Five short sentences, front-loaded with the purpose and threshold, followed by return shape and data-quality caveats. Every sentence carries information the agent needs.

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 fully covers the return shape (buy_exchange/buy_price, sell_exchange/sell_price, spread_pct), ranking, and filtering, and annotations cover the safety profile. Nothing essential is missing 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?

Schema coverage is 100% and the single optional `symbol` parameter is fully documented in the schema ('Omit for full matrix'). The description adds no further parameter semantics, so baseline 3 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?

States a specific resource (cross-venue spread-arbitrage opportunities for perpetual futures) with the qualifying condition (price gap >= 0.5%). Easily distinguished from siblings like perp_funding, perp_long_short and perp_open_interest, which cover different perp 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?

Gives clear usage context: results are pre-ranked and meant to be cited directly, and the schema documents that omitting symbol returns the full matrix. No explicit alternatives or when-not-to-use guidance, which keeps it from a 5.

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