By alexiolan
Run structured AI-orchestrated development pipelines for any project: brainstorm and plan features with architecture alignment, dispatch parallel agents for UI/data coding, execute browser tests on dev servers, systematically debug via root-cause analysis, and audit changes for quality/reuse. Supports local LLMs, Claude, Codex hybrids for cost savings.
npx claudepluginhub alexiolan/craft-skills --plugin craft-skillsFull design-first pipeline with Codex as a co-executor for data-layer tasks. Claude handles architecture and UI; Codex handles types, services, queries, schemas, enums, mappers, and bulk fixes. Use when you want cost relief via Codex without losing Claude's reasoning on UI and integration.
Cost-optimized craft variant: Qwen3.6-35B-A3B handles implementation and reviews locally, Opus orchestrates, Sonnet as fallback. Requires LM Studio running. Targets ~45-60% API cost reduction vs base /craft.
Generate or verify the project's one-time AESTHETIC_DIRECTION.md — a design-language contract used by ux-brief and design-review. Invoked automatically by architect/craft when UI work is planned and .claude/aesthetic-direction.md does not yet exist. Auto-generates without blocking; user can refine the file later.
Use when the user needs to plan and architect a new feature before implementation begins. This includes analyzing requirements, asking clarifying questions, and creating a detailed implementation plan aligned with the project's architecture. Invoke BEFORE any coding work starts.
Loaded at session start. Establishes awareness of craft-skills so the assistant invokes relevant skills before acting. Not invoked directly.
Use when a feature has been built and needs browser-based UI testing. Plans test scenarios, groups them into parallel batches, and dispatches multiple browser-tester agents simultaneously.
Same as /craft but with local LLM review steps enabled. Use when you have LM Studio running and want LLM-assisted spec/plan/post-develop reviews. Preserves pre-1.1 craft behavior.
Full design-first pipeline with all three AI agents: Claude (architect + UI + integration), Codex (data-layer + bulk fixes), and local LLM (LM Studio, for exploration + review). Power-user mode. Optionally runs Codex adversarial review if codex-plugin-cc is installed.
Use when starting a new feature that needs thorough design exploration. This is the most comprehensive workflow: collaborative brainstorming with the user, then planning, then parallel agent development, then browser testing. Use for complex features, unclear requirements, or when the user wants to explore approaches before committing.
Use when investigating bugs, errors, failing tests, or unexpected behavior. Enforces systematic root-cause investigation BEFORE attempting any fix. Invoke this skill before writing any fix code.
Post-develop visual regression + design-contract audit. Starts the dev server, captures screenshots of changed UI routes, and dispatches a Haiku-vision agent to compare the result against .claude/aesthetic-direction.md and the feature's ux-brief.md. Flags regressions before browser-test runs. Escalates to Sonnet or Opus only when Haiku flags issues.
Use when an approved implementation plan exists and is ready to be executed. Initializes shared state, dispatches parallel developer agents, performs integration review, and runs full verification (lint, tsc, format, build).
Use when an approved implementation plan already exists (from craft, implement, or architect) and needs to be executed and tested. Combines develop + browser-test into a single pipeline.
Dispatch as a haiku agent to run code-review-graph queries. Handles graph freshness, embedding setup, semantic search, and targeted queries. Other skills should dispatch this as an agent rather than calling graph tools directly.
Use when implementing a feature with clear, well-understood requirements. Quick planning via architect agent, then parallel agent development, then browser testing. Faster than craft — use when requirements don't need deep exploration.
Dispatch as a haiku agent to run local LLM tasks. Handles the full lifecycle: availability check, model loading, script execution, result collection, and model unloading. Other skills should dispatch this as an agent rather than running LLM bash commands directly.
Use when auditing, improving, or maintaining project health — CLAUDE.md accuracy, memory hygiene, settings, plans, and pattern discovery. Invoke periodically or when the user asks to audit or improve their project configuration.
Generate or refresh .claude/reuse-index.md — a one-page inventory of the project's shared utilities, enums, hooks, and components that downstream implementer agents must consult before writing new code. Project-agnostic scan: no framework assumptions baked in. Invoke once per project (or when the shared surface changes meaningfully).
Use after implementation is complete to review changed code for reuse opportunities, quality issues, and architecture compliance. Identifies missed shared components, unnecessary complexity, and boundary violations.
Generate a structured UX brief for a feature before implementation — diagnosis + prioritized patches + success criteria — that downstream implementer agents (Sonnet, Qwen3.6, Haiku) execute without clarification. Invoked by architect/craft when the spec contains UI components. Solo frontend-design by default; combined mode (frontend-design + ui-ux-pro-max) for complex UI based on spec complexity tag.
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CodyMaster — 68+ AI agent skills for the full development lifecycle: TDD, debugging, quality gates, safe deploy, design system, UX, content factory, secret scanning, CRO, brainstorming, and skill orchestration.
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AI-powered development tools for code review, research, design, and workflow automation.
Production-ready Claude Code configuration with role-based workflows (PM→Lead→Designer→Dev→QA), safety hooks, 44 commands, 19 skills, 8 agents, 43 rules, 30 hook scripts across 19 events, auto-learning pipeline, hook profiles, and multi-language coding standards
Structured project planning and execution through brainstorm, spec, and build phases across three execution tiers: sequential, delegated sub-agents, and full agent teams
Use this agent when creating user interfaces, designing components, building design systems, or improving visual aesthetics. This agent specializes in creating beautiful, functional interfaces that can be implemented quickly within 6-day sprints. Examples:\n\n<example>\nContext: Starting a new app or feature design