- Updated all packages from ai@6.0.23 to ai@6.0.49
- Added pnpm override to ensure consistent version
- Created changeset for publishing affected packages
- @tpmjs/registry-search and @tpmjs/registry-execute use ESM syntax
- Move from serverExternalPackages to transpilePackages so Next.js
properly bundles and transpiles them
- Revert to static imports now that packages are bundled correctly
- Move @ai-sdk/devtools import to lazy dynamic import to prevent
module load failures in production environment
- Add try-catch around response.json() in client to handle
non-JSON error responses gracefully
- Display proper error message when server returns non-JSON response
- Light mode: pure white backgrounds (#FFFFFF) with high contrast
near-black text (#0A0A0A) for better readability
- Dark mode: clean neutral blacks (#0A0A0A base) instead of warm browns
- Borders use neutral grays instead of warm-tinted grays
- Status colors (success, warning, error, info) more saturated and vibrant
- Maintains copper accent color (#A6592D) as brand element
- Overall cleaner, more minimal feel with stronger contrast
- Create /api/skills/questions endpoint for listing questions with pagination
- Create /api/skills/questions/[id] endpoint for individual question details
- Add questions list page with filtering by skill
- Add question detail page with full answer, related tools, and similar questions
- Make activity feed cards clickable links to question detail
- Add "View all" link in SkillsSection
- Replace hardcoded purple/blue colors with primary/10 backgrounds
- Use text-primary for icons instead of hardcoded colors
- Use error tokens for error states instead of red-*
- Use ProgressBar component instead of custom div progress bars
- Use EmptyState component for empty activity feed
- Use Card components consistently with proper padding
- Fix TypeScript types in integration tests
Implements a skills endpoint that evolves through agent conversations:
- GET /:username/collections/:slug/skills - Returns markdown skill summary
- POST /:username/collections/:slug/skills - Ask questions, get RAG+LLM responses
Features:
- OpenAI text-embedding-3-large (3072 dims) for semantic similarity
- GPT-4.1-mini for response generation with RAG context
- Lazy seeding of synthetic questions on first access
- Cache hits for >95% similar questions
- Real-time skill graph updates (emergent skill taxonomy)
- Session support for multi-turn conversations
- Activity feed and stats APIs for UI
Database models: SkillQuestion, Skill, SkillSession, SkillQuestionSkill, SkillQuestionTool
Add abstract tool rendering infrastructure to @tpmjs/ui:
- ToolRenderer component with registry-based renderer lookup
- DefaultJsonRenderer as fallback with collapsible JSON display
- RegistrySearchRenderer for registrySearchTool results
- RegistryExecuteRenderer for registryExecuteTool results
- registerBuiltInRenderers() for idempotent initialization
Update Omega chat page to use new ToolRenderer:
- Replace inline ToolCallCard with ToolRenderer component
- Add helper functions to convert between ToolCall and ToolPart
- Remove unused expandedToolCalls state (managed internally)
Also add video file extensions to .gitignore
- Add /api/omega/settings/env-vars API endpoints for CRUD operations
- Add /omega/settings page with env var management UI
- Pass user env vars to tool execution in messages route
- Detect and warn about missing required env vars via SSE events
- Add EnvVarWarningBanner component to chat UI
- Update system prompt to document registry tools usage
- Improve auth flow on landing page with sign-in redirect
- Add Prisma models for conversations, messages, participants, tool runs, and user settings
- Create API endpoints for conversation CRUD and SSE message streaming
- Build landing page with sample prompts at /omega
- Build chat interface with real-time streaming at /omega/[conversationId]
- Integrate @tpmjs/registry-search and @tpmjs/registry-execute packages
- Use OpenAI GPT-4.1 Mini as the default model
- Create /:username/collections/:slug/usage.md endpoint
- Shows real-world usage patterns from test scenarios
- Filters out health check scenarios automatically
- Groups examples by tags for better organization
- Update skills.md to reference usage.md for usage examples
Implements batched generation to avoid Vercel 120s timeout for collections
with 60+ tools. Uses per-tool caching and recursive serverless invocations.
- Add ToolSkillsCache and SkillsGenerationJob models to schema
- Create tool-skills-generator.ts for per-tool markdown generation
- Create skills-summary-generator.ts for final pass summary/intro
- Update route handler with chunked generation logic
- Small collections (<20 tools) use original monolithic approach
- Large collections use 10-tool batches with progress tracking
Transform qualifying scenarios into marketing-ready use cases with:
- AI-generated titles, descriptions, ROI estimates, business value
- Persona/industry/category taxonomy for targeting
- Browseable feed with filtering and ranking
- SEO-optimized case study pages
- Daily cron job for generation and ranking
Database:
- Add Persona, Industry, Category lookup tables
- Add UseCase model with marketing content fields
- Add junction tables for personas/industries/categories
- Add SocialProof model for cached metrics
API:
- GET /api/use-cases - Global directory with filtering
- GET /api/use-cases/[id] - Individual use case details
- GET /api/public/users/[username]/collections/[slug]/use-cases
- POST /api/cron/use-cases - Nightly generation job
Frontend:
- /use-cases - Global feed with persona dropdown
- /use-cases/[slug] - SEO case study page
- /[username]/collections/[slug]/use-cases - Collection feed
- UseCasesFeed component - Sortable table component
- UseCaseCaseStudy component - Full case study layout
- Move use cases section above scenarios section on collection detail pages
- Add AppHeader and AppFooter to /docs/developers/guide page for consistent layout
- Remove undefined variable reference (run.conversation) in header
- Extract ExpandedRunDetails component to reduce JSX nesting
- Fix vitest configs: rename to .mjs and add ESM-compatible __dirname
- Inline tailwind base config to avoid module resolution issues
- Remove unused imports (Streamdown, viewMode state)
This fixes the Turbopack parsing error that was preventing the build.
- Inline tailwind config to resolve Turbopack import issues with @tpmjs/config
- Add exports field to @tpmjs/config package.json for proper module resolution
- Add @tpmjs/config to transpilePackages in Next.js config
Note: page.tsx has a pre-existing Turbopack parsing error at line 604
that needs to be addressed separately (it existed before these changes).
- Add new /docs/developers/guide page with comprehensive scenarios documentation
- Explain what scenarios are, why use them, and how they work
- Cover developer use cases (CI/CD, local testing, quality monitoring)
- Include comparison with traditional testing approaches
- Add to AppHeader developers dropdown menu
- Add Streamdown for markdown rendering
- Add Message interface for conversation typing
- Add viewMode state (chat/debug) for switching views
- Add conversation history section in expanded run details
- Show conversation in chat format (USER/ASSISTANT/TOOL messages)
- Add view mode toggle to switch between chat and raw JSON views
- Improve usage stats section to show — when data is missing
- Make evaluator field nullable in TypeScript interface
- Add optional chaining for run.evaluator?.verdict
- Add optional chaining for run.evaluator?.model
- Prevents TypeError when evaluator object is missing
- Make usage field nullable in TypeScript interface
- Add optional chaining for run.usage?.executionTimeMs
- Add optional chaining for run.usage?.totalTokens
- Prevents TypeError when usage object is missing
- Add optional chaining for run.timestamps?.createdAt
- Make timestamps.createdAt optional in interface
- Add null check for evaluator.reason
- Prevents TypeError when accessing undefined properties
- Add ShareButton component for Twitter/X sharing
- Refactor collection page to server component with generateMetadata
- Add proper OpenGraph and Twitter Card meta tags for social sharing
- Extract client-side logic to CollectionDetailClient component
- Add global scenarios explorer page at /scenarios
- Add scenario detail page with run history at /scenarios/[id]
- Add collection-scoped scenario detail page
- Add featured scenarios section to homepage
- Add useScenarios hook for data fetching
- Regenerate CLI manifest
- Create ScenariosSection component with scenario list, status badges, and metrics
- Allow generating new scenarios with AI (owner only)
- Allow running scenarios and showing run progress
- Display quality scores and pass/fail streaks
- Link to scenario detail pages for run history
- Replace simulated execution with real AI SDK generateText() calls
- Build tools from collection with executor config cascade
- Support multi-step tool execution with MAX_TOOL_STEPS limit
- Capture full conversation history, token usage, and execution time
- Use gpt-4.1-mini for consistent execution model
- Add /docs/scenarios page with comprehensive user guide
- Overview of what scenarios are
- Common archetypes for different tool types
- CLI commands: generate, list, run, test, info
- Quality scoring explanation
- CI/CD integration examples
- Rate limits documentation
- Add /docs/api/scenarios page with API reference
- List scenarios endpoint
- Get scenario details
- List collection scenarios
- Create scenario
- Generate scenarios with AI
- Run scenario
- Get run history
- Check prompt similarity
- Featured scenarios
- Error responses
