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

Annotations cover the safety profile (readOnly, idempotent, non-destructive, openWorld), but the description adds substantial context beyond them: it discloses that a live transfer simulation is run from a real holder, that the result is a hard canSell verdict with reasons, and — critically — the payment model ($0.08 per call over x402 on Base, prepaid x-credit-token header for unlimited calls, no free tier, no API key). That pricing/auth detail is exactly the kind of operational fact an agent needs and cannot get from 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?

Front-loaded with the core question and the decision context, and the bulk of the text is dense with substantive detail (three check types, payment terms, required input). It loses a point for rhetorical filler like 'Selling is where rugs hide' and the punchy hook, which add tone rather than information.

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 return-value documentation is not owed, yet the description still summarizes the verdict shape ('hard canSell verdict with reasons'). Combined with the three analysis dimensions and the full payment/auth model, an agent has enough to call it correctly. The only gap is any guidance on the optional `size` parameter's effect, which is minor given schema coverage.

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 the schema already documents both `address` (token contract address) and `size` (position size USD for the exit check). The description only restates that address is the required input and adds nothing about the optional size parameter or accepted formats. Baseline 3 is appropriate when the schema carries the parameter burden.

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 and resource: it answers whether a Base token can actually be sold, framed as a honeypot check with three named components (security simulation, live transfer simulation, exit liquidity). It's far more than a restatement of the name. However, it never explicitly distinguishes itself from close siblings like exit_liquidity, rug_score, or base_swap_validity — in fact it absorbs 'exit liquidity' as a sub-component, leaving the agent to infer the boundary.

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?

Gives a clear triggering context: 'Use when an agent must know it can SELL a Base token before it buys.' That is an actionable precondition. It stops short of naming when-not-to-use or pointing to a specific alternative tool, so it is clear context without explicit exclusions.

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