A
licenseA
qualityD
maintenanceKlarna-style product discovery for AI shopping agents. Makes product catalogs machine-readable so AI agents can search, compare, and purchase products programmatically.
6
24 PyPI
MIT
meta-search
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TDQS
B3.3/5.0
Scored across 11 tools
Disambiguation4/5
Most tools target distinct actions (search, compare, details, offers, registration status). The review trio (find_review_attributes, list_review_states, get_review_evidence) forms a staged pipeline that could momentarily confuse an agent, and search_product_docs vs get_product_details overlap in the 'product content' space, but descriptions clarify their roles.
Naming Consistency5/5
All names follow a consistent snake_case verb_noun pattern (get_, search_, compare_, find_, list_, register_). Verbs are used predictably for their action class with no style mixing.
Tool Count5/5
11 tools sit squarely in the ideal 3-15 range. Each tool maps to a distinct step in the search/compare/review/registration workflow, so no tool feels redundant or missing.
Completeness4/5
The surface covers the full lifecycle: guidance, search, compare, details, docs lookup, review analysis (attributes/states/evidence), offers, and registration with status. Minor gaps like search pagination or explicit seller comparison are absent but not blocking.
Maintenance
ActivityMaintained
ResponsivenessNo recent community issues