mcp-server

get_marketplace_item_history

Read-only

Get ONE listing item's action-log timeline — the sequence of events that acted on the product and its Koongo/channel state at each point, so you can explain WHY an item ended in its current state (e.g. it was created, changed, validated, pre-paired, submitted, rescheduled, removed, locked). Returns {itemId, returned, entries:[{createdAt, event, eventLabel, message, messageLabel, operation, operationLabel, koongoStatus, channelStatus}]} newest first. eventLabel/messageLabel/operationLabel are the human-readable rendering the Koongo UI shows (event name, plain-language explanation, operation title); event/message/ operation are the raw codes. Entries are process metadata only (no raw product values). item_id is the itemId from list_marketplace_items (the same id get_marketplace_item_report uses). Pair this with get_marketplace_item_report (current errors) to diagnose a failing product. marketplace_id is the integrationId from list_marketplaces. project_id is OPTIONAL (inferred for a single-project customer; project_id_required otherwise — then call list_projects).

Input Schema

TableJSON Schema

Name	Required	Description
`limit`	No	Max timeline entries to return (default 20, max 50).
`item_id`	Yes	The listing itemId (from list_marketplace_items).
`project_id`	No
`marketplace_id`	Yes	integrationId of the marketplace (from list_marketplaces).

TDQS

A4.9/5.0

Behavior5/5

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

The description adds substantial behavioral detail beyond the readOnlyHint=true annotation: it discloses the response structure, newest-first ordering, that entries contain only process metadata not raw product values, and the distinction between raw event codes and human-readable labels. This is far more than the annotations alone convey.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

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

The description is dense but every sentence contributes: purpose, return contract, field semantics, pairing recommendation, identifier provenance, and conditional parameter behavior. It is front-loaded with the core purpose and does not repeat the schema verbatim.

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 having no output schema, the description embeds a full return contract including nested entry fields and the labels/raw-code distinction. It covers how to obtain parameters, when the tool is needed, and what the output means, making it fully actionable for an agent.

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 75%, so the schema already documents three of four parameters. The description adds meaningful extra semantics by clarifying that item_id is the same id used by get_marketplace_item_report, that marketplace_id is the integrationId from list_marketplaces, and that project_id is optional only for single-project customers. This goes beyond the bare schema descriptions.

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 verb ('Get'), a precise resource ('ONE listing item's action-log timeline'), and the purpose (explaining WHY an item ended in its current state). It clearly differentiates from sibling tools like get_marketplace_item_report by focusing on the event timeline rather than current errors.

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?

Explicit guidance is given for when to use this tool: pair it with get_marketplace_item_report to diagnose a failing product. It also specifies where to obtain the required identifiers (item_id from list_marketplace_items, marketplace_id from list_marketplaces) and explains the optional project_id behavior, including when to call list_projects.

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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TDQS

A4.2/5.0

Disambiguation4/5

Tools are organized around distinct resources (ads, marketplaces, feeds, orders, rules, sources) with clear action verbs, and descriptions explicitly disambiguate near-pairs like get_feed_status vs ad_status or set_feed_filter vs set_feed_attribute_filter. A few similarly named status/action pairs (e.g. ad_status vs get_ad, run_ad_item_action vs run_ad_operation) require careful reading, but overall the purposes are separable.

Naming Consistency4/5

The overwhelming majority follow a consistent verb_noun snake_case pattern (list_*, get_*, create_*, set_*, run_*, test_*). Minor deviations like ad_status and marketplace_status (noun-based status tools) and koongo_knowledge break the pattern slightly, but the convention is clearly recognizable and predictable.

Tool Count1/5

At 105 tools, the surface is extreme and far beyond the 50+ threshold, even for a complex e-commerce integration domain. Much of the bloat comes from systematic triplication across ads, marketplaces, and feeds (e.g. three nearly identical map_*_attribute tools, three list_*_items, three get_*_report) that a generic resource parameter could have consolidated.

Completeness4/5

The toolset covers the full lifecycle of feeds, ads, marketplaces, order connections, rules, and imports, including create/read/update/delete, status monitoring, item-level actions, validation, repair, and restore. Minor gaps exist, such as no delete for standalone order connections and limited update capabilities for some entities, but these are workable and do not create dead ends for the core workflows.

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