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d9e4982
feat(v4): add core-next & cli-next packages with integration/E2E test…
Alive-Fish Apr 8, 2026
11d2510
feat(cli-next): add esbuild bundling for 97% faster startup
Alive-Fish Apr 8, 2026
ce39de5
fix(v4): rename core-next/cli-next packages to avoid pnpm workspace n…
Alive-Fish Apr 8, 2026
96a8404
fix(v4): resolve 10 CodeQL alerts — TOCTOU race conditions and file-d…
Alive-Fish Apr 8, 2026
148bff9
fix(v4): resolve remaining 9 CodeQL alerts — TOCTOU, Zip Slip, and qu…
Alive-Fish Apr 8, 2026
c12057c
fix(v4): add early '..' check on zip entry names to satisfy CodeQL Zi…
Alive-Fish Apr 8, 2026
e7db535
fix(ci): use braces in pnpm filter to include workspace dependencies
Alive-Fish Apr 8, 2026
2706548
fix(e2e): fix mocha TypeScript loading for e2e tests
Alive-Fish Apr 8, 2026
e18de22
docs: update instructions with EAFP filesystem pattern and archive se…
Alive-Fish Apr 8, 2026
188ec80
fix(ci): gitignore tsconfig.tsbuildinfo to prevent stale incremental …
Alive-Fish Apr 8, 2026
17f778d
ci: skip old e2e workflows for v4-only changes
Alive-Fish Apr 8, 2026
2b1f41d
fix(v4): add precommit hooks to core-next/cli-next and fix prettier v…
Alive-Fish Apr 9, 2026
6e9cb8b
fix(v4): swap postbuild order — prettier first, eslint last to resolv…
Alive-Fish Apr 9, 2026
e940fd9
fix(v4): remove redundant prettier from postbuild — eslint-plugin-pre…
Alive-Fish Apr 9, 2026
e328e40
ci(v4): remove format-check job — lint already validates formatting v…
Alive-Fish Apr 9, 2026
fbea547
fix(v4): remove eslint --cache from lint-staged to match CI
Alive-Fish Apr 9, 2026
e2ab6fd
fix(v4): clean tsbuildinfo in cli-next build and set ATK_BIN in e2e w…
Alive-Fish Apr 9, 2026
773066d
test(v4): add missing E2E tests for MCP scaffold, auth commands, add-…
Alive-Fish Apr 9, 2026
34d0ea5
fix(v4): resolve lint warnings in E2E tests and fix tsconfig.eslint.j…
Alive-Fish Apr 9, 2026
ed289a0
docs(v4): update dev-test-next skill and add lint-format skill
Alive-Fish Apr 9, 2026
513fa78
fix(v4): call registerBuiltinTemplates() in lifecycle.test.ts
Alive-Fish Apr 9, 2026
437aed6
perf(v4): parallelize lifecycle E2E tests across CI matrix
Alive-Fish Apr 9, 2026
58e8236
fix(v4): add CI-mode token provider for lifecycle E2E tests
Alive-Fish Apr 9, 2026
849f538
fix(v4): restore test env vars after azure/login overwrites them
Alive-Fish Apr 9, 2026
c54f797
feat(core-next): add inline specParser module with OpenAPI parsing, v…
Alive-Fish Apr 10, 2026
2d9986d
test(core-next): add unit and integration tests for specParser module
Alive-Fish Apr 10, 2026
da1152f
test(cli-next): add OpenAPI spec E2E tests and update instructions
Alive-Fish Apr 10, 2026
80994a9
fix(core-next): guard against prototype pollution in filterSpec path …
Alive-Fish Apr 10, 2026
d34b3e5
fix(cli-next): correct regenerate help test to use action subcommand
Alive-Fish Apr 10, 2026
067d96f
fix: resolve all 43 lifecycle E2E test failures
Alive-Fish Apr 10, 2026
3ab655f
refactor(core-next): remove 19 deprecated template descriptors (43 to…
Alive-Fish Apr 13, 2026
82fc62f
docs: update instructions and plan after descriptor cleanup
Alive-Fish Apr 13, 2026
05be3d4
fix(core-next): resolve lifecycle driver execution failures in CI E2E
Alive-Fish Apr 13, 2026
6391a5c
fix(core-next): mark untestable templates with testable: false
Alive-Fish Apr 13, 2026
30f9139
test(cli-next): fix E2E test robustness for CI
Alive-Fish Apr 13, 2026
34a270f
docs: update instructions, skills, and plan after E2E fix session
Alive-Fish Apr 13, 2026
2260d10
fix(core-next): resolve writeToEnvironmentFile key mismatch between d…
Alive-Fish Apr 13, 2026
68ea22a
fix(core-next): fix driver path resolution and output flow in executor
Alive-Fish Apr 13, 2026
307b498
fix: resolve lifecycle E2E test failures
Alive-Fish Apr 13, 2026
2694441
fix(core-next): resolve 4 lifecycle E2E test failure root causes
Alive-Fish Apr 13, 2026
34b8625
fix: resolve CI test failures in lifecycle tests
Alive-Fish Apr 14, 2026
7d79f0d
fix(core-next): make oauth/register baseUrl optional with apiSpecPath…
Alive-Fish Apr 14, 2026
cd882b7
fix(cli-next): fix resourceBaseName exceeding ARM maxLength:20 in E2E…
Alive-Fish Apr 14, 2026
ddd5194
fix(core-next): add runDotnetCommand driver, fix apiKey/oauth/aadApp …
Alive-Fish Apr 14, 2026
60789a6
fix(core-next): fix writeToEnvironmentFile key mismatch in oauth/regi…
Alive-Fish Apr 14, 2026
0010a2f
fix(core-next): resolve da/api-plugin-oauth unresolved env vars in aa…
Alive-Fish Apr 14, 2026
3412ce3
fix: resolve connector/graph E2E validate failure and improve ARM err…
Alive-Fish Apr 14, 2026
111be8f
fix(core-next): rename telemetry metric key from duration to duration…
Alive-Fish Apr 14, 2026
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79 changes: 79 additions & 0 deletions .agents/skills/continual-learning/SKILL.md
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---
name: continual-learning
description: Guide for implementing continual learning in AI coding agents — hooks, memory scoping, reflection patterns. Use when setting up learning infrastructure for agents.
---

# Continual Learning for AI Coding Agents

Your agent forgets everything between sessions. Continual learning fixes that.

## The Loop

```
Experience → Capture → Reflect → Persist → Apply
↑ │
└───────────────────────────────────────┘
```

## Quick Start

Install the hook (one step):
```bash
cp -r hooks/continual-learning .github/hooks/
```

Auto-initializes on first session. No config needed.

## Two-Tier Memory

**Global** (`~/.copilot/learnings.db`) — follows you across all projects:
- Tool patterns (which tools fail, which work)
- Cross-project conventions
- General coding preferences

**Local** (`.copilot-memory/learnings.db`) — stays with this repo:
- Project-specific conventions
- Common mistakes for this codebase
- Team preferences

## How Learnings Get Stored

### Automatic (via hooks)
The hook observes tool outcomes and detects failure patterns:
```
Session 1: bash tool fails 4 times → learning stored: "bash frequently fails"
Session 2: hook surfaces that learning at start → agent adjusts approach
```

### Agent-native (via store_memory / SQL)
The agent can write learnings directly:
```sql
INSERT INTO learnings (scope, category, content, source)
VALUES ('local', 'convention', 'This project uses Result<T> not exceptions', 'user_correction');
```

Categories: `pattern`, `mistake`, `preference`, `tool_insight`

### Manual (memory files)
For human-readable, version-controlled knowledge:
```markdown
# .copilot-memory/conventions.md
- Use DefaultAzureCredential for all Azure auth
- Parameter is semantic_configuration_name=, not semantic_configuration=
```

## Compaction

Learnings decay over time:
- Entries older than 60 days with low hit count are pruned
- High-value learnings (frequently referenced) persist indefinitely
- Tool logs are pruned after 7 days

This prevents unbounded growth while preserving what matters.

## Best Practices

1. **One step to install** — if it takes more than `cp -r`, it won't get adopted
2. **Scope correctly** — global for tool patterns, local for project conventions
3. **Be specific** — `"Use semantic_configuration_name="` beats `"use the right parameter"`
4. **Let it compound** — small improvements per session create exponential gains over weeks
138 changes: 138 additions & 0 deletions .agents/skills/frontend-design-review/SKILL.md
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---
name: frontend-design-review
description: >
Review and create distinctive, production-grade frontend interfaces with high design quality and design system compliance.
Evaluates using three pillars: frictionless insight-to-action, quality craft, and trustworthy building.
USE FOR: PR reviews, design reviews, accessibility audits, design system compliance checks, creative frontend design,
UI code review, component reviews, responsive design checks, theme testing, and creating memorable UI.
DO NOT USE FOR: Backend API reviews, database schema reviews, infrastructure or DevOps work, pure business logic
without UI, or non-frontend code.
acknowledgments: |
Design review principles and quality pillar framework created by @Quirinevwm (https://github.com/Quirinevwm).
Creative frontend guidance inspired by Anthropic's frontend-design skill
(https://github.com/anthropics/skills/tree/main/skills/frontend-design). Licensed under respective terms.
---

# Frontend Design Review

Review UI implementations against design quality standards and your design system **OR** create distinctive, production-grade frontend interfaces from scratch.

## Two Modes

### Mode 1: Design Review
Evaluate existing UI for design system compliance, three quality pillars (Frictionless, Quality Craft, Trustworthy), accessibility, and code quality.

### Mode 2: Creative Frontend Design
Create distinctive interfaces that avoid generic "AI slop" aesthetics, have clear conceptual direction, and execute with precision.

---

## Creative Frontend Design

Before coding, commit to an aesthetic direction:
- **Purpose**: What problem does this solve? Who uses it?
- **Tone**: minimal, maximalist, retro-futuristic, organic, luxury, playful, editorial, brutalist, art deco, soft/pastel, industrial, etc.
- **Constraints**: Framework, performance, accessibility requirements.
- **Differentiation**: What makes this distinctive and context-appropriate?

### Aesthetics Guidelines

- **Typography**: Distinctive fonts that elevate aesthetics. Pair a display font with a refined body font. Avoid Inter, Roboto, Arial, Space Grotesk.
- **Color & Theme**: Cohesive palette with CSS variables. Dominant colors + sharp accents > timid, evenly-distributed palettes.
- **Motion**: CSS-only preferred. One well-orchestrated page load with staggered reveals > scattered micro-interactions.
- **Spatial Composition**: Asymmetry, overlap, diagonal flow, grid-breaking elements, generous negative space OR controlled density.
- **Backgrounds**: Gradient meshes, noise textures, geometric patterns, layered transparencies, dramatic shadows, grain overlays.

**AVOID**: Overused fonts, cliched color schemes, predictable layouts, cookie-cutter design without context-specific character.

Match implementation complexity to vision. Maximalist = elaborate code. Minimalist = restraint and precision.

---

## Design Review

### Design System Workflow

**Before implementing:**
1. Review component in your Storybook / component library for API and usage
2. Use Figma Dev Mode to get exact specs (spacing, tokens, properties)
3. Implement using design system components + design tokens

**During review:**
1. Compare implementation to Figma design
2. Verify design tokens are used (not hardcoded values)
3. Check all variants/states are implemented correctly
4. Flag deviations (needs design approval)

**If component doesn't exist:**
1. Check if existing component can be adapted
2. Reach out to design for new component creation
3. Document exception and rationale in code

### Review Process

1. Identify user task
2. Check design system for matching patterns
3. Evaluate aesthetic direction
4. Identify scope (component, feature, or flow)
5. Evaluate each pillar
6. Score and prioritize issues (blocking/major/minor)
7. Provide recommendations with design system examples

### Core Principles

- **Task completion**: Minimum clicks. Every screen answers "What can I do?" and "What happens next?"
- **Action hierarchy**: 1-2 primary actions per view. Progressive disclosure for secondary.
- **Onboarding**: Explain features on introduction. Smart defaults over configuration.
- **Navigation**: Clear entry/exit points. Back/cancel always available. Breadcrumbs for deep flows.

---

## Quality Pillars

### 1. Frictionless Insight to Action

**Evaluate:** Task completable in ≤3 interactions? Primary action obvious and singular?

**Red flags:** Excessive clicks, multiple competing primary buttons, buried actions, dead ends.

### 2. Quality is Craft

**Evaluate:**
- Design system compliance: matches Figma specs, uses design tokens
- Aesthetic direction: distinctive typography, cohesive colors, intentional motion
- Accessibility: Grade C minimum (WCAG 2.1 A), Grade B ideal (WCAG 2.1 AA)

**Red flags:** Generic AI aesthetics, hardcoded values, implementation doesn't match Figma, broken reflow, missing focus indicators.

### 3. Trustworthy Building

**Evaluate:**
- AI transparency: disclaimer on AI-generated content
- Error transparency: actionable error messages

**Red flags:** Missing AI disclaimers, opaque errors without guidance.

---

## Review Output Format

See [references/review-output-format.md](references/review-output-format.md) for the full review template.

## Review Type Modifiers

See [references/review-type-modifiers.md](references/review-type-modifiers.md) for context-specific review focus areas (PR, Creative, Design, Accessibility).

## Quick Checklist

See [references/quick-checklist.md](references/quick-checklist.md) for the pre-approval checklist covering design system compliance, aesthetic quality, frictionless, quality craft, and trustworthy pillars.

## Pattern Examples

See [references/pattern-examples.md](references/pattern-examples.md) for good/bad examples of creative frontend and design system review work.

---

## Acknowledgments

Creative frontend principles inspired by [Anthropic's frontend-design skill](https://github.com/anthropics/skills/tree/main/skills/frontend-design). Design review principles and quality pillar framework created by [@Quirinevwm](https://github.com/Quirinevwm) for systematic UI evaluation.
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# Pattern Examples

## Creative Frontend (New Interfaces)

### Good: Clear Aesthetic Direction
- Landing page with brutalist aesthetic: Raw typography (Neue Haas Grotesk), stark black and white, asymmetric layouts
- Dashboard with organic theme: Rounded forms, earth tones, flowing animations, textured backgrounds

### Bad: Generic AI Aesthetic
- Overused fonts, cliched color schemes, centered content, generic card layouts

## Design System Review (Existing Work)

### Good: Frictionless
- Single primary button, clear task completion path

### Good: Quality Craft
- Uses design system with tokens, distinctive typography, keyboard accessible, tested in themes

### Bad: Quality Craft
- Hardcoded values, generic overused fonts, poor contrast in dark mode
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# Quick Checklist

Before approving any UI work:

## Design System Compliance
- [ ] Component verified in your Figma Design System
- [ ] Component implementation checked in your Component Library
- [ ] Figma Dev Mode specs followed (spacing, tokens, typography)
- [ ] Design tokens used (no hardcoded hex colors or pixel values)
- [ ] Token imports verified in code
- [ ] All variants/states implemented as designed in Figma
- [ ] Spacing measurements match Figma Dev Mode exactly
- [ ] Deviations documented with design approval

## Aesthetic Quality (especially for new designs)
- [ ] Clear conceptual direction (not generic overused fonts and cliched schemes)
- [ ] Distinctive typography (avoid overused fonts)
- [ ] Cohesive color palette with CSS variables
- [ ] Intentional motion (staggered reveals, hover states)
- [ ] Visual interest through composition (asymmetry, overlap, grid-breaking)
- [ ] Atmosphere through backgrounds (gradients, textures, patterns)
- [ ] Implementation complexity matches vision

## Frictionless
- [ ] Core task completable efficiently (≤3 interactions)
- [ ] Single clear primary action per view

## Quality Craft
- [ ] Uses design system components (verified in Figma)
- [ ] Design tokens used (no hardcoded values)
- [ ] Distinctive aesthetic (not generic overused fonts/cliched schemes)
- [ ] Accessible (Grade C minimum, Grade B ideal)
- [ ] Keyboard navigation complete
- [ ] Tested in light/dark/high contrast modes

## Trustworthy
- [ ] AI-generated content has disclaimer
- [ ] Error messages are actionable
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# Review Output Format

```
## Frontend Design Review: [Component/Feature Name]

### Context
- **Purpose**: What problem does this solve? Who uses it?
- **Aesthetic Direction**: [If new design: describe the bold conceptual direction]
- **User Task**: What is the user trying to accomplish?

### Summary
[Pass/Needs Work/Blocked] - [One-line assessment]

### Design System Compliance (if applicable)
- [ ] Component exists in [Your Figma Design System]
- [ ] Component usage verified in [Your Component Library]
- [ ] Implementation matches Figma specs (spacing, colors, typography)
- [ ] Uses design tokens (not hardcoded values) - verified in code
- [ ] All variants match design system options
- [ ] Spacing verified against Figma Dev Mode
- [ ] Documented exception if deviating from design system

### Aesthetic Quality (especially for new designs)
- [ ] Clear conceptual direction (not generic AI aesthetic)
- [ ] Distinctive typography choices
- [ ] Cohesive color palette with CSS variables
- [ ] Intentional motion and micro-interactions
- [ ] Spatial composition creates visual interest
- [ ] Backgrounds and visual details add atmosphere

### Pillar Assessment

| Pillar | Status | Notes |
|--------|--------|-------|
| Frictionless | 🟢/🟠/⚫ | Task completion efficient, primary action clear |
| Quality Craft | 🟢/🟠/⚫ | Design system compliant, aesthetic distinctive, accessible |
| Trustworthy | 🟢/🟠/⚫ | AI disclaimers present, errors actionable |

**Legend:** 🟢 Pass | 🟠 Needs attention | ⚫ Blocking issue

### Design Critique
**Verdict:** [Pass / Needs work / Reach out to design for more support]

**Rationale:** [Brief explanation based on pillar assessment, design system compliance, and aesthetic direction]

**Criteria:**
- **Pass**: All pillars 🟢 or minor 🟠 that don't block user tasks, design system compliant, clear aesthetic direction
- **Needs work**: Multiple 🟠 or any critical workflow issues, design system deviations, or generic aesthetic choices
- **Reach out to design for more support**: Any ⚫ blocking issues, fundamental pattern problems, major design system violations, or need for aesthetic direction

### Issues

**Blocking (must fix before merge):**
1. [Pillar/Design System/Aesthetic] Issue description + recommendation with link

**Major (should fix):**
1. [Pillar/Design System/Aesthetic] Issue description + pattern suggestion with reference

**Minor (consider for refinement):**
1. [Pillar/Design System/Aesthetic] Issue description + optional improvement

### Recommendations
- [Design system component to use with link]
- [Specific code change with design token reference]
- [Typography recommendation for better aesthetic direction]
- [Motion/animation suggestion]
- [Link to design system in Figma]
```
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# Review Type Modifiers

Adjust focus based on review context:

## PR Review
- **Focus**: Code implementation, design system component usage, design token usage, accessibility in code
- **Check**: Proper imports, design tokens used (not hardcoded), ARIA attributes present
- **Verify**: Component matches Figma specs using Dev Mode

## Creative Frontend Review
- **Focus**: Aesthetic direction, typography choices, visual distinctiveness, motion design
- **Check**: Clear conceptual intent, avoiding generic AI patterns, cohesive execution
- **Verify**: Implementation complexity matches vision (maximalist needs elaborate code, minimalist needs precision)

## Design Review
- **Focus**: User flows, interaction patterns, visual hierarchy, navigation, design system alignment
- **Check**: Task completion path, action hierarchy, progressive disclosure
- **Verify**: All components exist in design system or have documented exceptions

## Accessibility Audit
- **Focus**: Deep dive Quality Craft pillar
- **Check**: Keyboard testing, screen reader testing, contrast ratios, ARIA patterns
- **Test with**: Screen readers (NVDA, JAWS, Narrator), keyboard only, 200% zoom
- **Verify**: Design system accessibility features are properly implemented

## Design System Compliance Audit
- **Focus**: Deep dive design system usage
- **Check**: All components match Figma specs, design tokens used throughout, no hardcoded values
- **Test**: Compare implementation side-by-side with Figma using Dev Mode
- **Verify**: Component variants, spacing, colors, typography all match design system
- **Document**: Any deviations with rationale and plan to align
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