get_joint_recommendation

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

With no annotations, the description carries full burden for behavioral disclosure. It details how printer_id combined with kiln-pro installation narrows the clearance range based on calibration tier, and mentions the calibration_used block. It also notes the flat-range behavior for free users or omitted printer_id. This provides good transparency for a read-only recommendation 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 well-structured with a header paragraph and a parameter list in docstring style. It is informative but slightly verbose; every sentence adds value, but some redundancy exists (e.g., repeating the purpose in the first line and the docstring summary).

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 no output schema, the description explains the return behavior (clearance recommendations, calibration_used block) but does not specify the exact format (e.g., min/max values). It covers the main functionality and edge cases (free users, omitted printer_id), making it fairly complete for a 4-parameter tool.

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%, so the description must compensate. It explains each parameter: joint_type with examples, material_a and material_b with defaults, and printer_id with its effect. This adds significant meaning beyond the schema's minimal titles, though it could be improved by listing allowed enum values 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 clearly states the tool's purpose: 'Get recommended clearance settings for a joint type and material pairing.' This specific verb+resource pair distinguishes it from sibling tools like get_material_recommendation, which deals with materials rather than clearance settings.

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 explicit guidance on when to supply the printer_id parameter vs. omitting it, explaining the calibration effect and the fallback to historic flat-range behavior. However, it does not explicitly state when not to use the tool or provide alternatives for other recommendation needs.

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