ticket-ai
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TDQS
Scored across 8 tools
Most tools have clear, distinct purposes: house_style and learn_conventions are related but house_style reads the cache while learn_conventions populates it, which is well-communicated. review_ticket and review_draft are similar but review_draft explicitly targets unpublished drafts)Skip, so they are distinguishable. template_gaps and ticket_template serve different functions (gap analysis vs skeleton). The one potential confusion is review_ticket and review_draft, but the descriptions clearly differentiate them.
Most tools follow a noun_action pattern (e.g., learn_conventions, review_ticket, review_open_tickets), but there are inconsistent verb placements and some names are less clear: house_style is a noun phrase, ticket_template is a noun phrase, and template_gaps is a noun phrase without a verb. This mixes patterns (verb-first vs noun-first) and some names are not imperative verbs, which is inconsistent.
With 8 tools, the count is well within the ideal 3-15 range. Each tool has a specific role in the ticket lifecycle: learning conventions, retrieving templates, gathering context, reviewing drafts, reviewing created tickets, and reviewing the open board. No tool feels redundant, and the set is tightly scoped to the server's purpose of ticket style analysis and validation.
The tool set covers the full lifecycle: learning conventions (learn_conventions, house_style), generating templates (ticket_template), gathering context (ticket_context), checking gaps (template_gaps), and reviewing both drafts and existing tickets (review_draft, review_ticket), plus batch review (review_open_tickets). There are no obvious missing operations for the stated purpose; if anything, the coverage is thorough.