mcp-server

list_feed_templates

Read-only

List the PUBLIC Koongo feed TEMPLATES available for a project — the catalog of feed TYPES you can create from (the feedCode source for create_feed). These are NOT the customer's existing feeds (use list_feeds for those). Each item is {feedCode, name, type, fileType, channelCode, country}. project_id is OPTIONAL: omit it when the customer has a single project (it is inferred); if they have several you get project_id_required — call list_projects and pass one. Pass query as a BROAD coarse filter — ideally just the channel/marketplace name (e.g. 'google'); do NOT put country/format/language words in it, because feed codes are cryptic and a literal match will miss. Instead match the user's request (country e.g. CZ/Czech/Česko, format e.g. xml, type e.g. product vs promotions) against the STRUCTURED fields of the returned items yourself — word order and synonyms don't matter. Show the best matches, let the user confirm which feedCode, then call create_feed. Returns all matching templates in one call; not paginated.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`query`	No
`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 read-only and non-destructive, and the description adds behavioral details: the project_id_required error/inference behavior, that all matches are returned unpaginated, and the item field structure. It clearly states the scope ('PUBLIC templates') and no contradiction exists.

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?

Although longer than average, every sentence adds actionable information: differentiation, item structure, parameter guidance, and workflow. The text is front-loaded with the core definition and structured logically from purpose to usage to parameters.

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?

With no output schema, the description tells the agent exactly what items look like ({feedCode, name, type, fileType, channelCode, country}), how to handle both parameters, and what to do with results. No critical invocation details are missing.

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?

Schema has 0% description coverage, so the description carries the full burden. It fully defines query semantics (broad coarse filter, channel name, what to exclude) and project_id semantics (optional, inferred for single project, required and obtained via list_projects otherwise).

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?

Opens with a specific verb and resource: 'List the PUBLIC Koongo feed TEMPLATES available for a project'. It states the purpose as 'the catalog of feed TYPES you can create from' and explicitly differentiates from list_feeds, so an agent can distinguish it from siblings.

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?

States when to use list_feeds instead for existing feeds, and when to call list_projects and pass a project_id if project_id_required. Gives precise query strategy: use coarse channel names like 'google', avoid country/format/language words, and match structured fields manually. Also routes the resulting workflow to create_feed after user confirmation.

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.

Resources

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