mirror of https://github.com/catlog22/Claude-Code-Workflow.git synced 2026-03-25 19:48:33 +08:00

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catlog22 1e560ab8e8 feat: migrate all codex team skills from spawn_agents_on_csv to spawn_agent + wait_agent architecture

- Delete 21 old team skill directories using CSV-wave pipeline pattern (~100+ files)
- Delete old team-lifecycle (v3) and team-planex-v2
- Create generic team-worker.toml and team-supervisor.toml (replacing tlv4-specific TOMLs)
- Convert 19 team skills from Claude Code format (Agent/SendMessage/TaskCreate)
  to Codex format (spawn_agent/wait_agent/tasks.json/request_user_input)
- Update team-lifecycle-v4 to use generic agent types (team_worker/team_supervisor)
- Convert all coordinator role files: dispatch.md, monitor.md, role.md
- Convert all worker role files: remove run_in_background, fix Bash syntax
- Convert all specs/pipelines.md references
- Final state: 20 team skills, 217 .md files, zero Claude Code API residuals

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

2026-03-24 16:54:48 +08:00

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role, prefix, inner_loop, message_types

role

prefix

inner_loop

message_types

researcher

RESEARCH

false

state_update

Design System Researcher

Analyze existing design system, build component inventory, assess accessibility baseline, and retrieve industry-specific design intelligence via ui-ux-pro-max. Produce foundation data for downstream designer, reviewer, and implementer roles.

Phase 2: Context & Environment Detection

Input	Source	Required
Task description	From task subject/description	Yes
Session path	Extracted from task description	Yes
.msg/meta.json	/wisdom/.msg/meta.json	No

Extract session path and target scope from task description
Detect project type and tech stack from package.json or equivalent:

Package	Detected Stack
next	nextjs
react	react
vue	vue
svelte	svelte
@shadcn/ui	shadcn
(default)	html-tailwind

Use CLI tools (e.g., ccw cli -p "..." --tool gemini --mode analysis) or direct tools (Glob, Grep, mcp__ace-tool__search_context) to scan for existing design tokens, component files, styling patterns
Read industry context from session config (industry, strictness, must-have features)

Phase 3: Research Execution

Execute 4 analysis streams:

Stream 1 -- Design System Analysis:

Search for existing design tokens (CSS variables, theme configs, token files)
Identify styling patterns (CSS-in-JS, CSS modules, utility classes, SCSS)
Map color palette, typography scale, spacing system
Find component library usage (MUI, Ant Design, shadcn, custom)
Output: <session>/research/design-system-analysis.json

Stream 2 -- Component Inventory:

Find all UI component files; identify props/API surface
Identify states supported (hover, focus, disabled, etc.)
Check accessibility attributes (ARIA labels, roles)
Map inter-component dependencies and usage counts
Output: <session>/research/component-inventory.json

Stream 3 -- Accessibility Baseline:

Check ARIA attribute usage patterns, keyboard navigation support
Assess color contrast ratios (if design tokens found)
Find focus management and semantic HTML patterns
Output: <session>/research/accessibility-audit.json

Stream 4 -- Design Intelligence (ui-ux-pro-max):

Call Skill(skill="ui-ux-pro-max", args="<industry> <keywords> --design-system") for design system recommendations
Call Skill(skill="ui-ux-pro-max", args="accessibility animation responsive --domain ux") for UX guidelines
Call Skill(skill="ui-ux-pro-max", args="<keywords> --stack <detected-stack>") for stack guidelines
Degradation: when unavailable, use LLM general knowledge, mark _source: "llm-general-knowledge"
Output: <session>/research/design-intelligence.json

Compile research summary metrics: design_system_exists, styling_approach, total_components, accessibility_level, design_intelligence_source, anti_patterns_count.

Phase 4: Validation & Output

Verify all 4 output files exist and contain valid JSON with required fields:

File	Required Fields
design-system-analysis.json	existing_tokens, styling_approach
component-inventory.json	components array
accessibility-audit.json	wcag_level
design-intelligence.json	_source, design_system

If any file missing or invalid, re-run corresponding stream
Update <session>/wisdom/.msg/meta.json under researcher namespace:
- Read existing -> merge { "researcher": { detected_stack, component_count, wcag_level, di_source, scope } } -> write back

3.5 KiB Raw Blame History

Design System Researcher

Phase 2: Context & Environment Detection

Phase 3: Research Execution

Phase 4: Validation & Output

3.5 KiB

Raw Blame History