A
licenseNot graded
qualityA
maintenanceEnables AI assistants to research, plan, generate requirements, map codebases, create starter projects, manage tasks, and run multi-step software development workflows through MCP tools.
9 npm
MIT
WhenLabs/When
by WhenLabs-org
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TDQS
A4.7/5.0
Scored across 7 tools
Disambiguation5/5
Each tool has a clearly distinct purpose with no overlap: aware_sync handles AI context file generation, berth_check scans for port conflicts, envalid_validate validates environment files, stale_scan detects documentation drift, velocity_start_task/velocity_end_task manage task timing, and vow_scan audits dependency licenses. The descriptions clearly differentiate their domains and use cases.
Naming Consistency4/5
Most tools follow a consistent verb_adjective or verb_noun pattern (e.g., aware_sync, berth_check, envalid_validate, stale_scan, vow_scan), but the velocity tools use a verb_noun_task pattern which slightly deviates. The naming is generally readable and follows a predictable structure across the set.
Tool Count5/5
With 7 tools, the count is well-scoped for a development productivity server. Each tool addresses a specific, valuable aspect of project maintenance (context generation, port checking, env validation, docs drift, task timing, license scanning), and none feel redundant or out of place.
Completeness5/5
The tool set provides comprehensive coverage for development workflow automation: it includes tools for setup (aware_sync), pre-execution checks (berth_check, envalid_validate), quality assurance (stale_scan, vow_scan), and productivity tracking (velocity tools). There are no obvious gaps; agents can handle common development tasks end-to-end.
Maintenance
ActivityInactive
ResponsivenessUnresponsive