calculate_4pl_curve

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

With no annotations, the description carries the full burden of behavioral disclosure. It does not state whether the operation is read-only, what side effects (if any) occur, what the return format is, or whether there are computational constraints. This is a significant gap for a complex regression tool.

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 a single concise sentence with no filler. Every word contributes to the topic, though the phrase 'resolves... fields' is slightly awkward and could be clearer. It is appropriately short for the information it conveys.

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?

This tool is complex (non-linear regression) with no output schema and no annotations. The description provides no information about expected output, input validation, error conditions, or typical use cases. An agent would need more context to invoke this correctly, such as knowing that it returns curve parameters and requires paired arrays.

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%, and the description does not mention the parameters (concentrations, responses) or clarify their roles. The parameter names are somewhat self-explanatory, and the mention of 'dose-response' hints at their relationship, but the description fails to compensate for the lack of schema descriptions or specify required pairings or constraints.

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 identifies a specific analysis task (4PL non-linear regression) and names the resource ('sigmoidal dose-response fields'). However, the phrase 'resolves... fields' is imprecise and does not clarify whether it returns fitted parameters, goodness-of-fit, or a curve object. It does not differentiate from sibling tools like calculate_z_factor or calculate_lod_loq.

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?

No guidance is provided about when to use this tool versus alternatives. The description does not mention any prerequisites (e.g., matching array lengths, positive concentrations) or exclusions. It simply defines what the tool does without contextualizing its use.

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