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

With no annotations, the description carries the full burden and does so well: it flags the output as '[modeled]' (estimated, not exact), cites a backtest statistic, and explicitly disclaims predictive power. It does not cover refresh latency or rate limits, but the safety/interpretation context is strong.

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?

Dense but front-loaded: the core definition leads, then range, then the interpretive framing and disclaimer. Slightly run-on in the middle clause listing leverage tiers and exchanges, but no sentence is purely decorative.

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 and no annotations, the description adequately covers the return shape (per-bin notional, leverage-tier and exchange splits, cumulative long/short curves) plus the caveat about modeled estimates. Only refresh cadence and pagination/limits are unaddressed.

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 0%, so the description must compensate, and it does: range values (12h|1d|3d|7d), exchange options (binance/bybit/okx or 'all'), symbol example (BTCUSDT), and the leverage tiers exposed in the output. It doesn't explicitly tie each option list back to a named parameter, but the meaning is recoverable.

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?

Names a specific resource (liquidation map for a perp symbol) and precisely defines its shape: estimated notional of leveraged positions per price bin at liquidation price, split by leverage tier and exchange. The scope ('if price reaches this level, how much is there') is concrete enough to tell it apart from raw liquidations, cascades, or heatmap siblings.

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?

States the question it answers and explicitly routes live scoring to the sibling get_accuracy, giving the agent a clear primary use case. It stops short of naming when to prefer get_liquidation_heatmap or get_liquidations instead, so alternative selection is left partly to inference.

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