Get Company Items by SKUs (Batch)

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

Beyond annotations (readOnlyHint, idempotentHint, etc.), the description adds critical behavioral traits: the silent omission of unmatched SKUs and the restriction to 'standard items only'. This provides essential context for correct usage and error handling, fully leveraging the description's role to complement structured fields.

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 extremely concise at 4 sentences, front-loaded with the core purpose and constraints. Every sentence adds value: purpose, behavioral detail, and parameter listing. There is no fluff, and the structure (summary then args) is clear and scannable.

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 adequately covers return behavior (list of items, silent omission of unmatched SKUs) and constraints (standard items, max 100). For a read-only batch lookup tool, this is sufficient for an AI agent to understand its function and handle results. A perfect score would require explicit mention of the return format or error scenarios.

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 coverage is 100%, so the baseline is 3. The description repeats parameter meanings from the schema but adds no new semantic detail beyond 'standard items only' (which relates to items, not parameters). No additional constraints or formatting guidance are provided, so it meets but does not exceed the baseline for parameter semantics.

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 verb ('Returns'), resource ('list of saved items'), and criteria ('matching any of the supplied SKUs'). It also distinguishes from siblings by specifying 'standard items only' and the batch nature (max 100 SKUs), making it easy to differentiate from single-item lookup tools like machship_get_item_by_sku.

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 detecting misses: 'SKUs that don't match any item are silently omitted — compare returned Sku values against your input.' It also implies that this tool is for standard items only, hinting that complex items require other tools. However, it does not explicitly state when to prefer this over alternatives or list exclusions, keeping it from a perfect score.

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