Trading volume

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

This is a read-only public-data tool, and the description adds freshness and accuracy context that adds to the annotations ('may be delayed or wrong') plus an advice disclaimer. Together these note latency and data-quality caveats rather than repeating readOnlyHint.

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 return shape and mode distinction are front-loaded in the first sentence, and the constraints follow. The disclaimer clause is arguably padding but occupies only a few words.

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 no output schema, the description still enumerates what comes back (volume, high/low, last price, % change, top pools) and notes both modes and window constraints. Nothing an agent needs to call it correctly is missing.

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 description coverage is 100%, so parameters are already documented, and the description adds little beyond noting window_hours is single-pool only. That constraint is also in the schema, so the description provides only incremental value.

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 pairs a specific verb and resource ('24h volume, high/low, last price and % change') with the resource ('DeepBook pool') and explicitly covers both operating modes: single pool versus top pools. This distinguishes the tool from get_mid_price, get_pool_stats, and get_ohlcv.

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?

It clearly states the two modes and the condition that selects each ('if no pool is given', 'Set window_hours ... (single pool)'). It does not name competing siblings such as get_ohlcv or get_pool_stats, so the agent must infer which tool to choose for historical candles versus a snapshot.

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