recommend_settings

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

The description discloses key behaviors: it queries a learning database, returns aggregated recommendations plus raw settings, and details the conditional calibration overlay when kiln-pro is installed. It also notes recommendations are advisory and do not override safety limits. This is comprehensive given no annotations exist.

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 front-loaded with a clear summary, followed by filtering details, then the conditional calibration behavior, and a note. It is logically structured and reasonably concise, with no extraneous information, though the calibration section could be slightly condensed.

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?

The description covers core functionality and the calibration overlay, but lacks details on empty results or error handling. Without an output schema, the agent has limited understanding of the response structure beyond the calibration block. This leaves some gaps for an agent to navigate.

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?

The input schema only provides names and types with no descriptions. The description's 'Args' section adds examples and clarifies each parameter's role (e.g., filtering by printer, material, or file hash). This compensates for the 0% schema coverage, though it does not exhaustively specify constraints or allowed values.

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 first sentence clearly states the tool recommends print settings based on historical outcomes. It specifies filtering by printer, material, and file hash. However, it does not explicitly distinguish itself from sibling tools like infer_print_settings or predict_print_settings, leaving room for ambiguity.

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 no explicit guidance on when to use this tool versus alternatives. It does not mention scenarios to avoid or recommend this tool over others, leaving the agent to infer usage context from the tool's function alone.

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