SWEN AI
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TDQS
Scored across 7 tools
Each tool targets a distinct resource: model, tool, tutorial, news, or ranking. The model-related tools (get_model, list_ai_models, get_intelligence_ranking) are clearly differentiated by purpose, and search_tools vs search_news are separated by the object being searched.
All tool names follow a consistent verb_noun pattern using snake_case. The verbs (get, search, list) are applied predictably according to the action: get for single items, search for queries, and list for full catalogs or directories.
With 7 tools, the server is well-scoped for its domain covering models, tools, tutorials, and news. Each tool serves a clear purpose without redundancy, fitting comfortably within the ideal 3-15 range.
The news and model sections are complete with list/search and get operations, but tutorials only have a list (no get tutorial by slug) and tools only have search (no get tool by ID). These are minor gaps that agents can work around using the existing search/list results.