AgentSkillsCN

ui-fullflow-orchestrator

掌握端到端UI工作流的编排技能。将选型、美学设计、令牌生成、实施、重构、验收与自我评审串联成一条可执行的流水线,并生成统一的报告。

SKILL.md
--- frontmatter
name: ui-fullflow-orchestrator
description: Master orchestration skill for end-to-end UI workflow. Connects selection, aesthetics, token generation, implementation, refactor, acceptance, and self-review into an executable pipeline with unified reports.

UI Fullflow Orchestrator

Goal: upgrade 17 existing skills from "collaborative" to "serially executable".

SSOT

  • ../contracts/fullflow-handoff.md
  • ../contracts/quality-gates.md
  • ../contracts/reasoning-visibility.md
  • ../README.md
  • ../ui-codegen-master/SKILL.md
  • ../style-scope-guard/SKILL.md
  • ../svg-canvas-icon-engine/SKILL.md
  • ../../AI_UI_Skill_Design_Document.md
  • Frontend development specification document (Chinese source file in repo)

One-Click Pipeline Script

bash
bash skills/ui-fullflow-orchestrator/scripts/run_fullflow_pipeline.sh \
  --brief "SaaS dashboard with data readability and strong primary CTA" \
  --style-target "Dashboard header and core card area" \
  --scope-file "src/pages/dashboard.css" \
  --icon-mode auto \
  --icon-style outline \
  --framework react \
  --project-type saas-modern \
  --priority performance \
  --priority accessibility \
  --density comfortable

Default output directory: .fullflow-output/<timestamp>/

Artifacts:

  • flow.input.json
  • requirements.summary.json
  • requirements.prd.md
  • requirements.questions.md
  • style-profile.yaml
  • style.scope.lock.json
  • style.scope.checklist.md
  • icon.manifest.json (on demand)
  • icon.spec.md (on demand)
  • icon.sprite.svg (on demand)
  • selector.recommend.json
  • selector.evaluate.json
  • aesthetic.score.json
  • tokens.json
  • tokens.css
  • stage.status.json
  • quality.gates.md
  • self-eval.scorecard.json
  • optimization.plan.md
  • decision.trace.md (user-visible decision trace summary)
  • fullflow.report.md

Orchestration Flow

Follow the five-phase lifecycle from meta standards:

  • Phase 1 requirement analysis and design exploration
  • Phase 2 architecture planning and component design
  • Phase 3 code generation and implementation
  • Phase 4 self-review and refactor
  • Phase 5 acceptance and delivery
  1. app-workspace-guide: read current workspace baseline
  2. requirements-elicitation-engine: generate requirement draft, question list, style profile
  3. style-scope-guard: lock style-only change boundary and output scope lock
  4. ui-selector-pro: generate recommendation shortlist
  5. ui-selector-pro: run quantified evaluation for shortlist
  6. ui-aesthetic-coach: score brief aesthetics and suggest direction
  7. ui-aesthetic-coach: generate design tokens (JSON/CSS)
  8. svg-canvas-icon-engine: generate icon-system artifacts on demand
  9. ui-generation-workflow-runner: enter implementation
  10. ui-component-extractor + frontend-standards-enforcer: structure and standards optimization
  11. ui-acceptance-auditor + ui-self-reviewer: quality closure
  12. ui-codegen-master: final delivery convergence

Rules

  • Pipeline outputs must follow fullflow-handoff.md.
  • Stage status and quality gates must follow quality-gates.md.
  • Reasoning visibility must follow reasoning-visibility.md: output auditable decision summaries only, not private reasoning details.
  • If required inputs are missing (brief/framework/project-type), fail immediately with clear prompt.
  • If style_target is missing or style.scope.lock.json is not successfully locked, fail immediately.
  • When icon-mode=auto|on and icon requirements are detected, icon.manifest.json must be generated.
  • If requirements.summary.json has completeness_score < 70, mark requirement-completeness risk in report.
  • Must output quantitative scorecard (self-eval.scorecard.json) and optimization plan (optimization.plan.md) as iteration entry.
  • If script output conflicts with document heuristics, keep script output first and explain manual correction rationale in report.

Output Contract

  1. Pipeline execution result (success/failure)
  2. Artifact directory and report path
  3. Recommended library + recommended direction
  4. Stage status summary (five phases)
  5. Next skill chain to execute