mcp-server

get_project_profile

Read-only

Get a project's catalog product profile so you can recommend suitable sales channels for it. Returns {projectId, marketCategories:[{name, score, source}], stats:{productsCount, productsTotal, categoriesCount, avgPrice, medianPrice, currency, eanFillRate, eanBucket, metricsSyncedAt}}. marketCategories is the AI-detected catalog VERTICAL, ordered by score DESC — the first is the dominant vertical (e.g. 'Fashion & Accessories', 'Home & Decoration'); score is 0–1 confidence, source is ai|manual; the list is empty when the catalog has not been categorised yet. stats are catalog aggregates: avgPrice/medianPrice are in currency; eanFillRate is the 0–1 EAN/GTIN coverage and eanBucket its coarse form none|low|medium|high; a null means not-yet-computed (metricsSyncedAt shows how fresh the price/EAN figures are). Use the dominant vertical + price band + EAN coverage to suggest fitting marketplaces/ads: cross-reference list_marketplace_channels / list_ad_channels and propose ONLY channels whose available is true, then walk the create/configure wizard. Never invent channels that aren't in the catalog. 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	Default
`project_id`	No

TDQS

A5/5.0

Behavior5/5

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

Annotations already mark the tool as read-only and non-destructive. The description adds substantial behavioral context: the meaning of empty marketCategories lists, null handling for stats, field semantics (score confidence, source tags, freshness via metricsSyncedAt), and the optionality behavior of project_id. It fully discloses the tool's behavior beyond the safety hints.

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 long but every sentence serves a purpose: the lead states the goal, then the output schema is detailed with field semantics, then usage instructions follow. No fluff or repetition. It is front-loaded with the core purpose and ends with actionable guidance. The length is justified by the complexity of the tool.

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?

Given the rich output (no output schema provided), the description fully specifies the return structure, field meanings, null semantics, and how to use the data. It even references the prerequisite tool call for multi-project scenarios. An agent could confidently invoke and interpret the results without further documentation.

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

Parameters5/5

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

With one parameter (project_id) and 0% schema description coverage, the description compensates completely. It explains that project_id is optional for single-project customers and required otherwise, and directs to call list_projects when needed. This adds essential meaning that the bare schema (integer, exclusiveMinimum 0) does not provide.

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 opens with a clear, specific verb+resource: 'Get a project's catalog product profile so you can recommend suitable sales channels for it.' It states the primary purpose and the intended downstream use, distinguishing it from siblings like list_projects or get_marketplace. The tool's role in the channel-recommendation workflow is unambiguous.

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?

Includes explicit guidance on when to use the tool and how to act on its output: cross-reference list_marketplace_channels / list_ad_channels, propose only channels with available=true, and never invent channels. Also clarifies the conditional need for project_id and when to call list_projects instead. No ambiguity remains.

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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