lagrange_interpolate

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. The description only states what the tool does, without mentioning any behavioral traits such as error handling, numerical stability, input validation, or output format. For a mathematical interpolation tool with no annotations, this is a significant gap in transparency.

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 concise and front-loaded in a single sentence, with no wasted words. It efficiently conveys the core purpose and domain/category. However, it could be more structured by separating purpose from context or adding brief usage notes.

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?

Given the tool's complexity (mathematical interpolation with three parameters), no annotations, 0% schema coverage, and no output schema, the description is incomplete. It lacks details on behavior, parameters, output, and usage context, making it inadequate for an AI agent to confidently invoke the tool without additional assumptions.

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%, meaning none of the three parameters (x_points, y_points, x) are documented in the schema. The description doesn't add any parameter semantics beyond what's implied by the tool name—it doesn't explain what these arrays represent, their required lengths, or the meaning of 'x'. This leaves parameters largely 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?

The description clearly states the tool's purpose: 'Perform Lagrange polynomial interpolation through given points.' It specifies the verb ('perform'), resource ('Lagrange polynomial interpolation'), and scope ('through given points'), and includes domain/category context. However, it doesn't explicitly differentiate from sibling interpolation tools like 'linear_interpolate' or 'cubic_spline_interpolate' beyond mentioning 'Lagrange' specifically.

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?

The description provides minimal usage guidance. It mentions the domain ('numerical') and category ('interpolation'), which gives some context, but doesn't specify when to use Lagrange interpolation versus other interpolation methods available among siblings (like linear or cubic spline interpolation). No prerequisites, alternatives, or exclusions are mentioned.

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