Import Draft Preview

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, so the agent knows this is a safe, repeatable read operation. The description adds valuable behavioral context beyond annotations: the default modes, field truncation behavior, hard cap of 200 variants, and that active_rules is always present (even if empty). No contradictions with annotations.

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 appropriately sized and front-loaded with core functionality. Every sentence adds value: explaining modes, key fields, options behavior, and usage tips. It could be slightly more structured with bullet points for clarity, but there's minimal wasted text.

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's complexity (6 parameters, no output schema) and rich annotations, the description provides comprehensive context. It explains return data structure, behavioral defaults, and practical usage scenarios. The main gap is lack of explicit output format details, but the description compensates with field explanations and usage guidance.

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 100%, so the schema already documents all parameters thoroughly. The description adds some semantic context (e.g., explaining that sell_price is 'store listing price, $' and compare_at_price is 'strikethrough, $'), but most parameter details are already in the schema. Baseline 3 is appropriate when schema does the heavy lifting.

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: 'Reload preview for an import job' with specific details about two modes (compact and full) and what data they return. It distinguishes this from siblings like dsers_job_status (which likely shows status only) and dsers_product_import (which initiates imports).

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 use different modes: 'Use variant_detail='full' when agent needs compare_at or cost columns' and 'Set include_images=true... useful for visual SKU matching across suppliers.' It also distinguishes this from other tools by focusing on previewing import job data rather than finding, importing, or managing products.

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