Estimate market impact

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

Annotations declare readOnlyHint=true and openWorldHint=true, and the description reinforces this by explicitly stating no order is placed. It also discloses what the simulation returns. It doesn't mention latency, rate limits, or book staleness, but with annotations covering the safety profile this is solid added context.

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?

Two sentences, zero waste, with the core behavior and the safety guarantee front-loaded before the invocation hint.

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?

No output schema exists, but the description enumerates the return fields, which is the key missing piece for an output-less tool. Parameter guidance is adequately covered given 75% schema coverage. Minor omissions like rate limits or book freshness keep it from a 5.

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 75% and the description adds a meaningful constraint not encoded in the schema: 'Give size or notional_usd', clarifying these are alternative sizing inputs. The symbol description already routes to strike_list_markets, so the remaining gap is minor.

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 verb ('Simulates a market order against the live book') and enumerates the exact outputs: average fill price, worst price, slippage vs mid in bps, liquidity coverage. This clearly distinguishes it from the sibling read-only data tools like get_orderbook or market_snapshot, which do not simulate executions.

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 'without placing anything' clause establishes the safe, non-trading context and 'Give size or notional_usd' directs how to invoke. However, it offers no explicit when-to-use versus alternatives (e.g., use get_orderbook for raw depth vs this for a fill simulation), leaving some inference to the agent.

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