Designesy
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- AlicenseNot gradedqualityBmaintenanceEnables coding agents and CI to verify rendered web UIs against design token usage, layout constraints, and accessibility rules, returning concise pass/fail verdicts with actionable findings.MIT
- AlicenseNot gradedqualityBmaintenanceEnables AI coding agents to audit rendered web pages for design and UI defects by measuring geometry, styles, contrast and motion in a local browser and judging them against evidence-tiered rules. Findings come back as short, fixable items expressed in the project's own design tokens, while only sanitized numeric measurements leave the machine.Apache 2.0
- AlicenseNot gradedqualityAmaintenanceEnables AI coding assistants to generate bespoke design systems by synthesizing OKLCH color palettes, chamfer highlights and spring physics, teaching layout composition grammar, and returning micro-interaction primitives and component blueprints. Also audits JSX/TSX/HTML through a senior design director's lens to score and critique UI quality.23 npm1MIT
- AlicenseNot gradedqualityBmaintenanceProvides coding agents with local tools to inspect project UI inventories, propose and compare visual direction boards, compile versioned design contracts and DTCG tokens, retrieve section-specific blueprints, and audit running interfaces with browser evidence including screenshots, accessibility findings, and overflow measurements.MIT
- AlicenseAqualityBmaintenanceIt lets AI coding agents look up design tokens, component specifications, and prohibition rules on demand, then validate generated HTML or JSX with the same lint logic used by CI and editor hooks so violations are caught and corrected immediately. It also exposes the design constitution and rule sets as resources for reference during generation.6103 npm202MIT
- FlicenseNot gradedqualityBmaintenanceEnables AI coding agents to inspect a project's design tokens and component catalog, audit React/Tailwind files against seven static UI quality rules, score overall UI health, and apply auto-fixes that are re-audited and reverted on regression. It works both locally over filesystem access and remotely on raw TSX/JSX or CSS snippets passed directly as strings.-
TDQS
Scored across 17 tools
Each tool is scoped to a distinct artifact or verification engine, and the descriptions include explicit 'When NOT to use' cross-references that steer selection. There is mild residual overlap among the many _score tools (score, drift_score, readiness_score, monitor_score, report) and among the doc exports (llms_txt, llms_full_txt, agent_json), but the descriptions differentiate them well.
All names use a consistent designesy_ prefix with snake_case, and the seven scoring tools share a predictable _score suffix. The deviations are noun-only names (catalog, contract, report, guardrails, compare) mixed with suffix-bearing ones, which is a minor inconsistency but still readable and predictable.
17 tools is on the heavier side but each corresponds to a genuinely distinct design-intelligence capability (contract, tokens, motion, a11y, drift, readiness, monitor, compare, guardrails, exports). The scope is broad enough that the count is justified rather than padded.
The surface covers discovery, canonical contract, multiple export formats, many scoring dimensions, guardrail generation, monitoring, and comparison, with no write operations needed since it is read-only by design. The main gap is that designesy_catalog lists packages but there is no generic package-fetch tool for arbitrary ids beyond the main contract.