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slickdeals_search_advanced

Search Slickdeals deals with real pagination, facets, and numeric vote/comment/view counts. Filter results by category, store, or brand using facet IDs from a prior query.

Instructions

Search Slickdeals with real pagination, counts, and facets. Searches Slickdeals' modern search surface -- a richer alternative to GET /slickdeals/search's keyword-only search. Returns real pagination (page/total_pages/per_page/result_count), integer vote/comment/view counts (not parsed from free text), a fuller per-deal record (store id, discount percent, status flags), and facets -- Categories, Stores, and Brands available for the current query, each option carrying a value usable as category_id/brand_id/store_id. Facet values and counts are scoped to the current query, not a site-wide enumeration -- category_id/brand_id/store_id are passthrough filters (obtain a value from a prior response's own facets), not validated against a closed enum. sort defaults to relevance; other values are passed through unvalidated.

Input Schema

NameRequiredDescriptionDefault
qYesFree-text keyword query
pageNo1-based result page, default 1
sortNoSort order, default relevance
brand_idNoBrand facet id, from a prior response's own facets
store_idNoStore facet id, from a prior response's own facets
category_idNoCategory facet id, from a prior response's own facets

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.17.5

TDQS

A4.6/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and does so: it discloses what is returned (integer counts not parsed from free text, fuller per-deal records), that facet values/counts are query-scoped rather than site-wide, that category_id/brand_id/store_id are unvalidated passthrough filters, and that sort defaults to relevance but other values are passed through unvalidated.

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?

Front-loaded with purpose and the key differentiator, then details returns and filtering caveats. The dense em-dash clause is slightly run-on, but every sentence conveys actionable information with little waste.

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?

No output schema exists, so the description must explain returns — and it does (pagination fields, integer counts, per-deal record shape, facets for Categories/Stores/Brands). Combined with the facet-passthrough and sort caveats, an agent has everything needed to call it correctly.

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 100%, so the baseline is 3, but the description adds real meaning: it clarifies that facet ids are passthrough values sourced from a prior response rather than a closed enum, and that sort's default is relevance while other values are unvalidated. This goes beyond the terse 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?

States a specific verb (Search) and resource (Slickdeals) with explicit scope: 'real pagination, counts, and facets.' It directly distinguishes itself from the sibling slickdeals_search by positioning as 'a richer alternative to GET /slickdeals/search's keyword-only search,' so an agent can choose between them without opening schemas.

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

Usage Guidelines4/5

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

Names the alternative (the keyword-only search) and the condition that selects this tool (richer results with pagination/facets), and instructs that facet ids should be obtained from a prior response's own facets. It stops short of explicit when-not-to-use cases, but the routing context is clear.

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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