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

Goes well beyond the annotations (readOnly/idempotent/non-destructive): it discloses the fill model (bonding-curve reserves from the recorded tape, including curve fees and the copy's own price impact), the latency grid, the returned verdict categories, and pricing ($0.03/call, 10 free/day, x402 payment-required result). It also clarifies that upstream errors return isError and are not charged.

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?

Front-loads the core question and the mechanism, then layers simulation details, output, verdict, and operational notes (cost, errors). Dense but mostly non-redundant; the motivating line about wallets that look great on their own PnL earns its place as rationale, though the prose runs long.

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?

Given an output schema exists, the description need not explain returns, yet it summarizes PnL/win-rate/ROI per latency and the verdict anyway. Combined with cost, error behavior, and the when-to-use hook, 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 every parameter is already documented with ranges, defaults and the exit enum. The description reinforces the meaning ('last 1-14 days', 'sells when the leader sells') but adds no syntax or semantics beyond what the schema provides. Baseline 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?

States a specific verb+resource (replays a wallet's pump.fun entries/exits) and frames it with a concrete question ('Would copying this wallet have made money?'). It explicitly distinguishes itself from sibling tools by naming pump_wallet and smart_money as the upstream steps, so an agent can place it in the workflow without opening the schema.

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?

'When to use: After pump_wallet or smart_money, to check copying survives realistic delay' gives both the trigger condition and the alternatives it complements. It also states cost and error semantics, leaving no routing or invocation ambiguity.

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