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- Implement tests for AssociationHighlight, DashboardToolbar, QueuePanel, SessionGroupTree, and TerminalDashboardPage to ensure proper functionality and state management. - Create tests for cliSessionStore, issueQueueIntegrationStore, queueExecutionStore, queueSchedulerStore, sessionManagerStore, and terminalGridStore to validate state resets and workspace scoping. - Mock necessary dependencies and state management hooks to isolate tests and ensure accurate behavior.
198 lines
7.7 KiB
Markdown
198 lines
7.7 KiB
Markdown
# Agent Instruction Template -- Team Frontend
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Base instruction template for CSV wave agents. The orchestrator dynamically customizes this per role during Phase 1, writing role-specific versions to `role-instructions/{role}.md`.
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## Purpose
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| Phase | Usage |
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|-------|-------|
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| Phase 1 | Coordinator generates per-role instruction from this template |
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| Phase 2 | Injected as `instruction` parameter to `spawn_agents_on_csv` |
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---
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## Base Instruction Template
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```markdown
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## TASK ASSIGNMENT -- Team Frontend
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### MANDATORY FIRST STEPS
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1. Read shared discoveries: <session-folder>/discoveries.ndjson (if exists, skip if not)
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2. Read project context: .workflow/project-tech.json (if exists)
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---
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## Your Task
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**Task ID**: {id}
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**Title**: {title}
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**Role**: {role}
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**Pipeline Mode**: {pipeline_mode}
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**Scope**: {scope}
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**Review Type**: {review_type}
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### Task Description
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{description}
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### Previous Tasks' Findings (Context)
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{prev_context}
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---
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## Execution Protocol
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1. **Read discoveries**: Load <session-folder>/discoveries.ndjson for shared exploration findings
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2. **Use context**: Apply previous tasks' findings from prev_context above
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3. **Execute task**: Follow role-specific instructions below
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4. **Share discoveries**: Append exploration findings to shared board:
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```bash
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echo '{"ts":"<ISO8601>","worker":"{id}","type":"<type>","data":{...}}' >> <session-folder>/discoveries.ndjson
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```
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5. **Report result**: Return JSON via report_agent_job_result
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### Discovery Types to Share
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- `tech_stack_detected`: {stack, framework, ui_lib} -- Tech stack identification
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- `design_pattern_found`: {pattern_name, location, description} -- Existing design pattern
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- `token_generated`: {category, count, supports_dark_mode} -- Design token category created
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- `file_modified`: {file, change, lines_added} -- File change performed
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- `issue_found`: {file, line, severity, description} -- Issue discovered
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- `anti_pattern_violation`: {pattern, file, line, description} -- Anti-pattern detected
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- `artifact_produced`: {name, path, producer, type} -- Deliverable created
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---
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## Output (report_agent_job_result)
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Return JSON:
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{
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"id": "{id}",
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"status": "completed" | "failed",
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"findings": "Key discoveries and implementation notes (max 500 chars)",
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"artifacts_produced": "semicolon-separated paths of produced files",
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"qa_score": "",
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"qa_verdict": "",
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"error": ""
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}
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```
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---
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## Role-Specific Customization
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The coordinator generates per-role instruction variants during Phase 1. Each variant adds role-specific execution guidance to Step 3.
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### For Analyst Role
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```
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3. **Execute**:
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- Detect tech stack from package.json (react, nextjs, vue, svelte, html-tailwind)
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- Detect existing design system via Glob: **/*token*.*, **/*.css
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- Retrieve design intelligence via ui-ux-pro-max skill:
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- Full design system: Skill(skill="ui-ux-pro-max", args="<industry> <keywords> --design-system")
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- UX guidelines: Skill(skill="ui-ux-pro-max", args="accessibility animation responsive --domain ux")
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- Tech stack guide: Skill(skill="ui-ux-pro-max", args="<keywords> --stack <detected-stack>")
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- Fallback if skill unavailable: generate from LLM general design knowledge
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- Analyze existing codebase patterns (color palette, typography, spacing, components)
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- Optional: WebSearch for "<industry> web design trends best practices"
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- Compile design-intelligence.json with: _source, industry, detected_stack, design_system, ux_guidelines, stack_guidelines, recommendations
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- Write requirements.md summarizing all requirements
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- Output to <session-folder>/artifacts/analysis/
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```
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### For Architect Role
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```
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3. **Execute**:
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- Load design-intelligence.json from analyst output
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- Generate design token system (design-tokens.json) with categories:
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- color: primary, secondary, background, surface, text, CTA (light + dark mode)
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- typography: font families, font sizes (scale)
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- spacing: xs through 2xl
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- border-radius: sm, md, lg, full
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- shadow: sm, md, lg
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- transition: fast, normal, slow
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- Use $type + $value format (Design Tokens Community Group)
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- Generate component specs in component-specs/ directory:
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- Design reference (style, stack)
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- Props table (name, type, default, description)
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- Variants table
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- Accessibility requirements (role, keyboard, ARIA, contrast)
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- Anti-patterns to avoid
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- Generate project structure (project-structure.md) using stack-specific layout
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- Output to <session-folder>/artifacts/architecture/
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```
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### For Developer Role
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```
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3. **Execute**:
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- Load design tokens, component specs, and project structure from architect output
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- Generate CSS custom properties from design-tokens.json:
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- color -> --color-*, typography -> --font-*, --text-*, spacing -> --space-*
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- Add @media (prefers-color-scheme: dark) override for color tokens
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- Implement components following specs and coding standards:
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- Use design token CSS variables -- never hardcode colors/spacing
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- All interactive elements: cursor: pointer
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- Transitions: 150-300ms via var(--duration-normal)
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- Text contrast: minimum 4.5:1 ratio
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- Include focus-visible styles for keyboard navigation
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- Support prefers-reduced-motion
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- Responsive: mobile-first with md/lg breakpoints
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- No emoji as functional icons
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- Self-validate: scan for hardcoded colors, missing cursor-pointer, missing focus styles
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- Auto-fix where possible
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- Output to src/ directory (codebase files) + implementation summary
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```
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### For QA Role
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```
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3. **Execute**:
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- Load design intelligence and design tokens for compliance checks
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- Collect files to review based on review_type:
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- architecture-review: <session>/artifacts/architecture/**/*
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- code-review: src/**/*.{tsx,jsx,vue,svelte,html,css}
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- final: src/**/*.{tsx,jsx,vue,svelte,html,css}
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- Execute 5-dimension audit:
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- Dim 1 Code Quality (0.20): file length, console.log, empty catch, unused imports
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- Dim 2 Accessibility (0.25): alt text, labels, headings, focus styles, ARIA
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- Dim 3 Design Compliance (0.20): hardcoded colors, spacing, anti-patterns
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- Dim 4 UX Best Practices (0.20): cursor-pointer, transitions, responsive, states
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- Dim 5 Pre-Delivery (0.15): final checklist (code-review/final types only)
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- Calculate weighted score: sum(dimension_score * weight)
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- Determine verdict: score >= 8 AND critical == 0 -> PASSED; score >= 6 AND critical == 0 -> PASSED_WITH_WARNINGS; else -> FIX_REQUIRED
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- Write audit report to <session-folder>/artifacts/qa/
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- Set qa_score and qa_verdict in output
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```
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---
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## Quality Requirements
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All agents must verify before reporting complete:
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| Requirement | Criteria |
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|-------------|----------|
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| Files produced | Verify all claimed artifacts exist via Read |
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| Files modified | Verify content actually changed |
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| Findings accuracy | Findings reflect actual work done |
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| Discovery sharing | At least 1 discovery shared to board |
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| Error reporting | Non-empty error field if status is failed |
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| QA fields | qa_score and qa_verdict set for QA role tasks |
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---
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## Placeholder Reference
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| Placeholder | Resolved By | When |
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|-------------|------------|------|
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| `<session-folder>` | Skill designer (Phase 1) | Literal path baked into instruction |
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| `{id}` | spawn_agents_on_csv | Runtime from CSV row |
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| `{title}` | spawn_agents_on_csv | Runtime from CSV row |
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| `{description}` | spawn_agents_on_csv | Runtime from CSV row |
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| `{role}` | spawn_agents_on_csv | Runtime from CSV row |
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| `{pipeline_mode}` | spawn_agents_on_csv | Runtime from CSV row |
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| `{scope}` | spawn_agents_on_csv | Runtime from CSV row |
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| `{review_type}` | spawn_agents_on_csv | Runtime from CSV row |
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| `{prev_context}` | spawn_agents_on_csv | Runtime from CSV row |
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