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damurka

jumia-vendor-center

by damurka

sync_products

Reconcile your desired product data with live Jumia listings and push only changed price, stock, or status fields. Preview planned actions with dry-run, then submit batched feeds when ready.

Instructions

Reconcile your source of truth (an ERP export, a spreadsheet you've already parsed to JSON, etc) against what's live on Jumia right now, and push only the fields that actually changed - instead of you hand-writing separate create/update/price/stock calls.

desired: [{"sellerSku": "...", "price": 12000, "currency": "NGN", "stock": 50, "status": "ACTIVE"}, ...] (extend with brand/category/attributes if you also want update_products diffing - this baseline covers the highest-churn fields: price, stock, status.)

Looks up each sellerSku via list_products, diffs against desired, and by default (dry_run=true) returns the planned actions WITHOUT calling anything - review the plan first. Set dry_run=false to actually submit the price/stock/status feeds (batched, respecting the documented ~1000-item-per-feed cap) and get back the resulting feedIds.

Returns {matched, not_found: [sellerSku...], plan: {price: [...], stock: [...], status: [...]}, feed_ids: {...} (only when dry_run=false)}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
desiredYes
dry_runNo
shop_idNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A4.7/5.0
Behavior5/5

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

With no annotations provided, the description fully discloses behavior: it looks up sellerSku via list_products, diffs against desired, defaults to dry_run=true without side effects, and only submits batched feeds when dry_run=false. The return shape is also specified, so an agent understands what will happen and what it will get back.

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 detailed but well-structured: purpose, example, execution behavior, and return format are all present. It is somewhat dense with parenthetical asides, but every part contributes useful operational context.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

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

The absence of both annotations and an output schema means the description alone must cover behavior and returns. It does so well for a complex sync/diff tool, though shop_id semantics and failure/error behavior are not addressed.

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 0%, so the description must compensate. It thoroughly explains the desired array with a JSON example and clarifies dry_run semantics, but it does not explicitly describe shop_id. This is a minor gap because the key required parameter is well-specified.

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 states a specific action: reconcile a source of truth against Jumia and push only changed fields. It distinguishes itself from separate create/update/price/stock calls, making its role among the siblings clear.

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

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explicitly frames the tool as a replacement for hand-writing separate create/update/price/stock calls and notes the dry_run-first workflow. It also signals when to extend to update_products diffing, giving practical when-to-use guidance.

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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