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OyaAIProd

DSers MCP Product

by OyaAIProd

Import Draft Preview

dsers_product_preview
Read-onlyIdempotent

Reload product import preview to review variant details, pricing, and stock status. Choose compact or full view to inspect sell price, compare-at price, cost, and quantities.

Instructions

Reload preview for an import job. Two modes: compact (default) returns [name, sell, qty] for ALL variants — lightweight. full returns [name, sell, compare_at, cost, qty, supplier_qty] for 3 variants by default. Always includes price_summary: {sell:{min,max}, cost:{min,max}, zero_stock_count, low_stock_count, variants_count}. Key fields: sell_price (store listing price, $), cost (supplier price, $), compare_at_price (strikethrough, $). options: array of {name, values[], values_count} — values truncated to 10 by default, set show_all_options=true for full list. active_rules: currently applied rules (always present, {} if none). Use variant_detail='full' when agent needs compare_at or cost columns.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
job_idYesJob ID returned by dsers_product_import.
variant_limitNoMax variants in skus table. Compact default: all. Full default: 3. Hard cap: 200.
variant_detailNocompact (default): columns [name, sell, qty], shows ALL variants. full: columns [name, sell, compare_at, cost, qty, supplier_qty], shows 3 by default.
variant_offsetNoStart index for variant/SKU listing (0-based). Default: 0.
show_all_optionsNoShow all option values instead of truncating to 10. Use before applying option_edits.
Behavior5/5

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

Annotations already declare readOnly, idempotent, and non-destructive. The description adds substantial behavioral context: default truncation of options to 10, always-present active_rules and price_summary, column differences between modes, and hard cap of 200. No contradiction 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.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is dense but well-organized, covering modes, field meanings, defaults, and usage tips. It is slightly long but every sentence adds value, and information 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.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite lacking an output schema, the description thoroughly specifies the return structure (price_summary fields, options structure, active_rules) and behavior differences between modes. It fully compensates for the missing output schema and covers the tool's complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3. The description adds meaning beyond schema by explaining key field semantics (e.g., sell_price is store listing price, cost is supplier price), clarifying variant_limit defaults, and advising when to use show_all_options. This extra context elevates the score.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: 'Reload preview for an import job.' It specifies the resource (import job) and action (reload preview), and distinguishes between compact and full modes, making the purpose unambiguous and distinct from sibling tools that handle imports, updates, or status checks.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

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 each variant_detail mode ('Use variant_detail='full' when agent needs compare_at or cost columns') and explains default behaviors for variant_limit. However, it does not explicitly compare to sibling tools like dsers_job_status, so overall tool selection context is only implicit.

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

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