abc_xyz_classify

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

No annotations provided, so description carries full burden. Discloses required input format, dependency on caller-supplied data, and a blocking issue with CDS-view. Does not mention side effects or error conditions, but the core behavioral traits are covered.

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?

Two sentences, front-loaded with the main purpose and return format. The second sentence adds essential dependency and constraint context. No wasted words.

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 and two complex parameters, the description covers inputs, output format, dependencies, and a known limitation. Could mention whether tool is read-only or requires permissions, but overall fairly complete for a classification 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 description must compensate. It explains that valueItems require {id, value} and demandItems require {id, demandSeries} with demandSeries being an array of numbers. Adds business context about ABC/XYZ and the blocking issue, significantly adding value beyond the schema.

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?

Clearly states the tool classifies materials by ABC (value/Pareto) and XYZ (demand variability) and returns a combined 9-cell matrix label like 'AX'. This distinguishes it from sibling tools like calc_reorder_point or forecast_demand which focus on different inventory analyses.

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?

Provides context on when to use: requires caller-supplied valueItems and demandItems. Notes a limitation that demand series cannot be sourced automatically due to a blocked CDS-view, giving practical guidance. Does not explicitly list exclusions or alternatives but implies usage scenarios.

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