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

Annotations already establish read-only, idempotent, non-destructive behavior, but the description adds substantial context beyond them: pricing ($0.01/call, 10 free/day, x402 payment-required response), error behavior (isError, not charged), refresh cadence (every 6 hours), and methodology (empirical rates, shrinkage toward coarser buckets). It also discloses what is bucketed from the first 60 seconds, which helps an agent interpret results.

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 dense but front-loads the core purpose and then uses labeled sections for usage, price, and errors. It is longer than a minimal definition, but nearly every sentence contributes operational or behavioral context, with only the bucket-methodology sentence being somewhat detailed relative to the rest.

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?

An output schema exists, so the description does not need to explain return values, and annotations cover safety. The description still supplies the missing operational context an agent needs: cost, free-tier behavior, payment-required outcome, error semantics, refresh cadence, and when to defer to launch_scan.

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 100% for the single `mint` parameter, including the Base58 format and length constraint, so the schema already carries parameter documentation. The description does not add format or validation guidance beyond the schema; its detail is about the computed statistic rather than the input, making 3 the appropriate baseline.

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 precise verb and resource: computing the probability that a pump.fun launch graduates, using empirical outcomes from comparable launches plus lift over the ~3% base rate. The mechanism and scope are specific enough that an agent can distinguish it from generic token lookups like pump_token or pump_launches.

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?

Explicitly says 'When to use: For graduation probability only' and names launch_scan as the broader alternative that bundles this check with others. This gives both the selecting condition and the sibling/alternative route.

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