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* feat(ai): scaffold pen-ai-skills package
* feat(ai): add pen-ai-skills core types
* feat(ai): add Vite plugin for skill file compilation
* feat(ai): add budget module with token estimation and category-priority trimming
* feat(ai): add skill loader with phase filtering and test injection
* feat(ai): add skill resolver with phase filter, intent match, and dynamic injection
* feat(ai): migrate all prompt content to skill files
Extract prompt content from 7 TypeScript source files into 27 Markdown
skill files with proper frontmatter. Each file contains phase, trigger,
priority, budget, and category metadata for the skill resolution engine.
Planning: decomposition, design-type
Generation: jsonl-format, jsonl-format-simplified, schema, layout,
text-rules, overflow, style-defaults, variables, design-system,
design-code, design-md
Validation: vision-feedback
Maintenance: local-edit, incremental-add, style-consistency
Domains: landing-page, dashboard, mobile-app, form-ui, cjk-typography
Knowledge: role-definitions, design-principles, icon-catalog,
copywriting, examples
* feat(ai): add document context memory module
* feat(ai): add generation history memory module
* feat(ai): wire memory loading into skill resolver
Add memory field to ResolveOptions and load documentContext/generationHistory
into AgentContext with per-phase limits (planning:5, maintenance:3, others:0).
Export memory utility functions from package index.
* refactor(ai): use resolveSkills('planning') in orchestrator
Replace ORCHESTRATOR_PROMPT import with resolveSkills() from pen-ai-skills.
The planning phase system prompt is now resolved dynamically from skill
files instead of a static constant.
* refactor(ai): use resolveSkills('generation') in sub-agent
Replace SUB_AGENT_PROMPT + designPrinciples concatenation with
resolveSkills() from pen-ai-skills. The generation phase system prompt
is now resolved dynamically with flag-based skill filtering for
variables and design.md context.
* refactor(ai): use resolveSkills('validation') in design validation
Replace the 70-line inline VALIDATION_SYSTEM_PROMPT constant with a
lazy resolver function that loads the validation prompt from pen-ai-skills
skill files at call time.
* refactor(mcp): use skill registry for design prompt sections
* refactor(ai): remove old prompt files replaced by pen-ai-skills
Delete prompt files whose content has been migrated to the
pen-ai-skills package:
- ai-prompt-sections.ts (section registry, triggers, builders)
- orchestrator-prompts.ts (orchestrator + sub-agent prompts)
- design-system-prompts.ts (design token generation prompt)
- design-code-prompts.ts (HTML/CSS code-gen prompt)
- design-principles/ directory (5 principle files + index)
Consolidate role-definitions/ 8 sub-files into index.ts
(registerRole calls are runtime behavior, must be preserved).
Move buildDesignMdStylePolicy into ai-prompts.ts. Strip migrated
constants (PEN_NODE_SCHEMA, DESIGN_EXAMPLES, ADAPTIVE_STYLE_POLICY,
CHAT_SYSTEM_PROMPT, DESIGN_GENERATOR_PROMPT, etc.) from ai-prompts.ts.
Add pen-ai-skills alias to mcp:compile esbuild script.
* docs: add pen-ai-skills to architecture documentation
* fix(mcp): use h3 v2 createEventStream API for SSE endpoint
event.node.res was removed in h3 v2. Migrate to createEventStream
which handles SSE headers, streaming, and cleanup automatically.
* chore: update package versions and add pen-ai-skills to Dockerfile
- Bump version for multiple packages to 0.5.2, including pen-ai-skills, pen-codegen, pen-core, pen-figma, pen-renderer, pen-sdk, and pen-types.
- Add pen-ai-skills package to Dockerfile for inclusion in the build process.
- Update TypeScript configuration to ensure proper file inclusion.
- Modify GitHub Actions workflow to trigger on version tags.
- Enhance AI-related functionality by integrating resolveAgentModel for dynamic model resolution in chat and generation APIs.
* refactor: clean up unused imports and improve dynamic content handling
- Removed unused imports from various files, including SkillMeta and ResolvedSkill from types.test.ts, and estimateTokens from resolve-skills.ts.
- Updated the dynamic content injection function to use a more concise parameter in the regex replacement callback.
* chore: enhance build and CI workflows with skill generation
- Added a new script to generate the skill registry during post-installation in package.json.
- Updated the GitHub Actions workflows to include steps for compiling the CLI and generating the skill registry, ensuring all necessary components are built and ready for deployment.
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Co-authored-by: Fini <fini.yang@gmail.com>
11 lines
435 B
TypeScript
11 lines
435 B
TypeScript
import { defineEventHandler, createError } from 'h3'
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import { getSyncDocument } from '../../utils/mcp-sync-state'
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/** GET /api/mcp/document — Returns the current canvas document for MCP to read. */
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export default defineEventHandler(() => {
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const { doc, version } = getSyncDocument()
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if (!doc) {
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throw createError({ statusCode: 404, statusMessage: 'No document loaded in editor' })
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}
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return { version, document: doc }
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})
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