suggest_spool_swaps

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

With no annotations, the description carries the full burden for behavioral traits. It implies read-only behavior by stating it 'analyses' and 'suggests,' but does not explicitly confirm non-destructiveness, permission requirements, or other behavioral aspects like impact on system state.

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 very concise: a short paragraph with a clear summary sentence, explanatory detail, and an 'Args' section for the parameter. Every sentence adds value, and the structure is front-loaded with the core purpose.

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 has 1 parameter (complex object) and no output schema, the description adequately covers the input requirements but lacks description of the output format (e.g., structure of swap suggestions). It is fairly complete but could be improved by specifying what the tool returns.

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 description adds meaning beyond the schema by specifying that each job dict should contain 'material_type' and 'required_grams'. Since schema coverage is 0%, this provides essential guidance that the raw schema lacks.

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 specific verb+resource: 'Suggest minimal spool swaps to run all queued jobs.' It explains the analysis and distinguishes from siblings like 'suggest_material_for_order' or 'suggest_printer_for_job' by focusing on physical spool changes for queued jobs.

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 implies usage when you have queued jobs and want to minimize spool swaps, but it does not explicitly state when to use this tool versus alternatives (e.g., 'suggest_material_for_order'), nor does it mention prerequisites or when not to use it.

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