check_token

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

While annotations already declare readOnlyHint=true and destructiveHint=false, the description adds substantial behavior beyond that: a per-call cost of $0.001, that the probability is a MEASURED frequency rather than a raw score (with a pointer to get_scorecard), and the notable limitation that it 'does not name holders.' These are meaningful behavioral disclosures not available in the annotations.

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?

Every phrase earns its place: cost, purpose, output composition, cost-optimization routing, and limitations are each covered in a tightly packed 4-sentence definition. The core question is front-loaded, with operational details layered afterward. Dense but not bloated.

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?

For a single-parameter tool with an output schema present, the description covers the semantic output (verdict, concentration, collapse speed), pricing, the calibration source (get_scorecard), its relationship to more expensive siblings, and a key limitation (holder anonymity). Nothing critical is missing for an agent to decide when and how to call it.

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% — the single `mint` parameter already documents itself as 'Solana token mint, base58.' The description adds no additional syntax or format details beyond the schema, landing at the baseline 3.

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?

The description leads with the core purpose — 'Is this Solana token dangerous?' — and then specifies the deliverable: a calibrated rug verdict with a measured probability, concentration facts, and band-collapse speed. It distinguishes itself from siblings by positioning this tool as the cheap gating check that decides whether inspect_token, token_identity, or token_report is worth the cost.

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 usage guidance is provided: 'Cheapest call, run it on every token; it decides whether inspect_token, token_identity or token_report is worth paying for.' This tells the agent when to invoke this tool (as a first pass on every token) and frames the alternatives as downstream follow-ups conditional on this tool's output.

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