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

Annotations already declare readOnly/idempotent/non-destructive, and the description goes well beyond them: pricing ($0.01/call, 10 free/day, x402 payment-required result), freshness (rebuilt every 6 hours), shrinkage behavior on thin samples, and error semantics (isError on invalid input or upstream failure, uncharged). This is unusually rich disclosure for a read-only tool.

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-loaded with the core purpose and method, followed by freshness, when-to-use, price, and errors. The sentences are dense but each earns its place; slightly long, though nothing is truly redundant.

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?

Output schema exists, so return-value explanation is unnecessary. The description still covers the modeling approach, data freshness, cost, error behavior, and routing to alternatives, leaving no material gap for calling the tool correctly.

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?

Only one parameter with 100% schema description coverage, so the schema fully documents the required mint and its Base58 format. The description's bucket details (unique buyers, buy SOL, dev buy over the first 60s) describe the model inputs rather than parameter usage, adding no semantics beyond the schema. Baseline 3 applies.

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 resource (pump.fun launch graduation probability) and a specific method (empirical rates from comparables with lift over the ~3% base rate). It distinguishes itself from siblings by scoping to 'graduation probability only' and naming launch_scan as the broader alternative. An agent can tell this apart from pump_launches, pump_token, or pump_pulse without opening a 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?

Explicit 'When to use: For graduation probability only' with a named alternative (launch_scan on the MAD Synapse risk server) that bundles it with other checks. This is a genuine when/when-not routing statement, not implied guidance.

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