Crypto liquidations: daily long/short totals per symbol and exchange

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

The annotations only indicate read-only and open-world behavior, so the description carries the burden of explaining data provenance and interpretation. It adds strong context: events are recorded from specific exchange stream collectors, are a floor rather than estimates, are finalized per UTC day, and history begins on a known date and grows daily. This goes well beyond what annotations or schemas disclose.

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 front-loaded with the call trigger, then provides a dense but efficient second sentence covering output, units, granularity, source, caveat, and history. Every clause adds useful information and there is no repetition of the title or schema.

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?

There is no output schema, so the description must explain what the agent can expect in the result, and it does: daily long/short totals in USD, per symbol and exchange, one row per finalized UTC day, plus the data availability start date. The call pattern is also complete: an optional symbol filter and a default days window are both covered. Nothing essential is missing for a tool of this complexity.

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 100% coverage for both parameters: days has a default and range, symbol has a pattern and meaning. The description reinforces the output granularity (per day, symbol, exchange) but does not add any new parameter-level semantics beyond what the schema documents, so the baseline score 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 states exactly what the tool does: returns daily long and short liquidation totals in USD per symbol and exchange for crypto futures. It also names concrete user queries ('how much was liquidated', 'whether longs or shorts got flushed', 'liquidation history'), making the purpose unmistakable even among many sibling tools.

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 says when to call the tool ('Call this when the user asks how much was liquidated...', 'or for liquidation history'). It does not name alternatives or state when not to use it, such as pointing to get_liquidation_cascades for cascade-specific analysis, so it falls just short of full routing guidance.

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