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ihavealotofguap

oskelly-mcp

Get result count and available facets

oskelly_search_facets
Read-onlyIdempotent

Run a search to get total matches and available facets, revealing which filters to apply and result volume before fetching products.

Instructions

Run the same search as oskelly_search_products but return the total result count plus the list of facets available for that result set (their codes, names, types, hot values and the price range present) instead of the products. Use this to discover which filters make sense before drilling down, or to count matches cheaply without fetching items.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNo1-based page number.
priceNoPrice range in RUB; at least one of lower/upper must be set. NOTE (verified live): the backend matches this per size/SKU, not against the card price. A product matches if ANY of its sizes is priced inside the range, and the returned card `price` is the cheapest size — so a card price may fall outside the requested range. Compare against `sizePriceRange` on each result to see the actual span.
queryNoFull-text query, e.g. "gucci сумка". Omit to browse the catalog without a text query.
sizeIdsNoSize value ids (from oskelly_filter_values code='size').
sortingNoNEW = newest first, PRICE_ASC / PRICE_DESC = by price, SCORE_DESC = by relevance (only meaningful with a query), PERSONALIZED = site's own ranking.NEW
verboseNoReturn the raw upstream payload instead of the compact projection. Much larger.
brandIdsNoBrand ids (from oskelly_list_brands or oskelly_filter_values code='brand').
modelIdsNoModel ids (from oskelly_filter_values code='model').
sellerIdsNoRestrict results to specific seller account ids.
pageLengthNoItems per page (1-60). Keep small to limit response size.
categoryIdsNoLeaf/branch category node ids (from oskelly_category_tree).
baseCategoryNoRoot segment node id from the category tree: 2 = Женское, 105 = Мужское, 188 = Детское, 366 = Лайфстайл. These are real tree node ids — read them from oskelly_category_tree rather than assuming. Omit to search all segments.
conditionIdsNoCondition ids: 1 = Новое с биркой, 2 = Отличное, 3 = Хорошее.
extraFiltersNoEscape hatch: raw filter entries merged into the request body verbatim, for facet codes discovered via oskelly_search_facets that this schema does not name yet.
collectionIdsNoCollection ids: 5 = Новая коллекция, 6 = Sale, 7 = Аутлет.
sellerTypeIdsNoSeller type ids (from oskelly_filter_values code='sellerType').
booleanFiltersNoBoolean facet toggles, e.g. {"sale": true, "vintage": true}. Available codes: sale, oskellyChoice, streetwear, newCollection, inStock, outlet, carry_over, celebrity_wardrobe, investment, vintage, brandNew, resale, exclusiveSelection, currentCollection
boutiqueLocationTagIdsNoOSKELLY boutique location ids (from oskelly_filter_values code='boutiqueLocationTag').
Behavior4/5

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so safety is covered. The description adds behavioral context beyond annotations by specifying exactly what is returned (total count, facet codes/names/types/hot values/price range) and that it avoids fetching items, which is useful for cost expectations.

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?

Two front-loaded sentences: the first states exactly what the tool does, the second gives the primary use case. There is zero filler or redundancy.

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?

Despite having 18 parameters and no output schema, the description explains the returned facet fields and the use case, which is sufficient for a read-only facet-discovery tool. The schema covers parameters exhaustively, and the tool's purpose is simple enough that no further behavioral detail is needed.

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

Parameters3/5

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

Schema description coverage is 100%, so the input schema fully documents all 18 parameters. The description itself adds no parameter-level semantics, but it does not need to because the schema does the heavy lifting. Baseline 3 applies.

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 runs the same search as oskelly_search_products but returns the total result count and available facets instead of products. This distinguishes it from its sibling and specifies the exact resource and action.

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?

Explicitly tells the agent when to use it: to discover which filters make sense before drilling down or to count matches cheaply without fetching items. It also names the sibling alternative (oskelly_search_products), making the choice unambiguous.

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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