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

With no annotations, the description carries the full burden, and it does disclose the algorithm (linear fit through the last two points) and the rounding rule (4 decimals), which are genuinely useful behavioral facts. It omits error behavior for malformed or insufficient input, and the only payment context is the trial-call blurb rather than auth requirements.

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 and dense: the computational definition comes first, followed by the rounding rule. The trial-call emoji blurb is promotional padding but short, so the overall structure is still efficient.

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 two-parameter numeric tool with no output schema and no annotations, the definition covers the algorithm but not the input encoding or edge-case behavior. An agent could call it, but would likely guess wrong about the points format on the first attempt.

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 0% for two string parameters, so the description must compensate. It implies x is the evaluation point and points is a collection of [x,y] pairs, but never states the accepted string encoding (JSON array? CSV? delimiter?), leaving the most failure-prone detail undocumented.

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 outcome: 'Extrapolates y at x linearly through the last two [x,y] points and rounds y to 4 decimals.' That is precise enough to distinguish it from a generic math tool, though it never contrasts itself with the nearby interpolation/lerp siblings, so the agent must infer the difference from the name alone.

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?

There is no statement of when to use this versus alternatives such as x402-interpolate, x402-interpolation, or x402-lerp. Usage is only implied by the word 'extrapolation', and no prerequisites (e.g., needing at least two points) are given.

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