A
licenseB
qualityB
maintenanceTurns raw project ideas into polished, cost-aware first prompts for AI coding agents by recommending high-leverage open-source tools and cost-saving techniques.
1
5 npm
MIT
archify-mcp
by Tai-DT
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TDQS
A3.5/5.0
Scored across 26 tools
Disambiguation3/5
Most tools map to distinct planning domains, but smart_recommend, recommend_stack, compare_tech, analyze_compatibility, and recommend_dual_stack all touch stack selection and could be confused. Tool descriptions clarify their specific purposes, but an agent still faces meaningful overlap when choosing among them.
Naming Consistency5/5
All 26 tools consistently follow a verb_noun snake_case pattern such as plan_testing, design_database, and estimate_project. The verbs vary semantically, but the naming convention is uniform and predictable across the entire toolset.
Tool Count3/5
26 tools is on the heavy side, just above the 16-25 borderline range defined in the rubric. Each tool covers a distinct planning artifact and full_analysis aggregates them, but the set could be tightened by consolidating several overlapping recommendation and estimation tools.
Completeness5/5
The toolset covers the full architecture-planning lifecycle from project analysis, features, stack selection, architecture, database, security, and cost to estimation, roadmap, boilerplate, testing, DevOps, scalability, team, integrations, and monetization. There are no obvious dead ends, and full_analysis acts as a closed-loop pipeline for complete project assessment.
Maintenance
ActivityInactive
ResponsivenessNo issues