## Summary
- **Consolidate logic function services**: Remove
`LogicFunctionMetadataService` and consolidate all logic function CRUD
operations into `LogicFunctionFromSourceService`, with a new
`LogicFunctionFromSourceHelperService` for shared validation/migration
logic
- **Introduce typed conversion utils following the skill pattern**: Add
`fromCreateLogicFunctionFromSourceInputToUniversalFlatLogicFunctionToCreate`
and `fromUpdateLogicFunctionFromSourceInputToFlatLogicFunctionToUpdate`
that convert DTO inputs directly to flat entities
(`UniversalFlatLogicFunction` / `FlatLogicFunction`), replacing the
previous intermediate `UpdateLogicFunctionMetadataParams` indirection
- **Simplify `CodeStepBuildService`**: Remove ~100 lines of manual
duplication logic by delegating to
`LogicFunctionFromSourceService.duplicateOneWithSource`
- **Remove completed 1-17 migration**: Delete
`MigrateWorkflowCodeStepsCommand` and associated utils that migrated
workflow code steps from serverless functions to logic functions
- AI still often forgets to update the code step after creating it.
Adding a next step
- Starting by loading logic functions, so it avoids creating code steps
when a function exists
- Fix create complete workflow logic. Should not create code steps
directly
⚠️ **AI-generated PR — not ready for review** ⚠️
cc @FelixMalfait
---
## Changes
### System prompt improvements
- Explicit skill-before-tools workflow to prevent the model from calling
tools without loading the matching skill first
- Data efficiency guidance (default small limits, use filters)
- Pluralized `load_skill` → `load_skills` for consistency with
`load_tools`
### Token usage reduction
- Output serialization layer: strips null/undefined/empty values from
tool results
- Lowered default `find_*` limit from 100 → 10, max from 1000 → 100
### System object tool generation
- System objects (calendar events, messages, etc.) now generate AI tools
- Only workflow-related and favorite-related objects are excluded
### Context window display fix
- **Bug**: UI compared cumulative tokens (sum of all turns) against
single-request context window → showed 100% after a few turns
- **Fix**: Track `conversationSize` (last step's `inputTokens`) which
represents the actual conversation history size sent to the model
- New `conversationSize` column on thread entity with migration
### Workspace AI instructions
- Support for custom workspace-level AI instructions
---------
Co-authored-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com>
## Context
Introduces a middleware that automatically sets the workspace auth
context in AsyncLocalStorage for HTTP requests, making it available
throughout the request lifecycle without explicit parameter passing.
The motivation behind this change is to reduce boilerplate and simplify
the developer experience when working with workspace data in HTTP
request handlers.
The Problem (Before)
Every HTTP request handler that needed to access workspace data had to:
- Extract auth-related info from decorators (@AuthWorkspace(),
@AuthUserWorkspaceId(), etc.) in controller/resolver and pass down to
services
- Build or pass the authContext explicitly (sometimes with type
assertion which was flaky)
Then call executeInWorkspaceContext(authContext, async () => { ... })
## Changes
- Add WorkspaceAuthContextMiddleware that extracts auth context from the
request and stores it in AsyncLocalStorage
- Register middleware for GraphQL, metadata, and REST routes (runs after
hydration middlewares)
- Simplify executeInWorkspaceContext signature: fn is now the first
parameter, authContext is optional second
- If authContext is not provided, it's automatically retrieved from the
storage (set by middleware)
- Update all callers (~120 files) to use the new parameter order
- Fixes a bug in search where system auth context was used, bypassing
RLS feature.
## Summary
- Replace the agent search mechanism with a new skills-based system
- Add a `skills` module with predefined skill definitions that the AI
can load on demand
- Remove specialized agents (workflow-builder, data-manipulator,
dashboard-builder, metadata-builder, researcher), keeping only the
helper agent
- Add `recordReferences` to workflow creation tool for chip linking in
the UI
## Changes
### New Skills Module
- `skill-definitions.ts` - Contains 5 skill definitions with detailed
instructions
- `skills.service.ts` - Service to get skills by name
- `load-skill.tool.ts` - Tool for AI to load skills explicitly
### Removed
- `agent-search.tool.ts` - Replaced by skill loading
- Specialized agent definitions (converted to skills)
### Updated
- Chat execution now shows skill catalog in system prompt
- Workflow creation returns `recordReferences` for UI linking
## Test plan
- [ ] Verify AI can load skills using `load_skill` tool
- [ ] Verify skill content is returned correctly
- [ ] Verify workflow creation shows clickable chip in chat
- [ ] Verify helper agent still works
## Context
Following https://github.com/twentyhq/twenty/pull/16399
Now using the new global orm manager everywhere and returning a
GlobalDatasource/WorkspaceDatasource based on a feature flag.
This means we now need to wrap all our ORM calls within
executeInWorkspaceContext callback (at least for now) so the global
datasource can dynamically hydrate its context via the new store (the
global datasource does not store anything related to workspaces as it is
now a unique singleton). If feature flag is off it still uses local data
stored in the workspace datasource.
## Summary
This PR significantly simplifies the AI chat architecture by removing
complex routing/planning mechanisms and introduces clickable record
links in AI responses.
## Changes
### AI Chat Architecture Simplification
- **Removed** the entire `ai-chat-router` module (~850 lines) including:
- Strategy decider service
- Plan generator service
- Complex routing logic
- **Removed** agent execution planning services (~700 lines):
- `agent-execution.service.ts`
- `agent-plan-executor.service.ts`
- `agent-tool-generator.service.ts`
- **Added** centralized `ToolRegistryService` for tool management:
- Builds searchable tool index (database, action, workflow tools)
- Provides tool lookup by name
- Supports agent search for loading expertise
- **Added** `ChatExecutionService` as simple replacement:
- Includes full tool catalog in system prompt
- Pre-loads common tools (find/create/update for company, person,
opportunity, task, note)
- Uses `load_tools` mechanism for dynamic tool activation
- Enables native web search by default
### Record References in AI Responses
- Added `recordReferences` field to tool outputs for create, find, and
update operations
- Implemented `[[record:objectName:recordId:displayName]]` syntax for AI
to reference records
- Created `RecordLink` component that renders clickable chips with
object icons
- Integrated record link parsing into the markdown renderer
- Users can now click directly on created/found records in AI responses
### Workflow Agent Fixes
- Fixed cache invalidation issue when creating agents in workflows
- Added default prompt for workflow-created agents to prevent validation
errors
- Relaxed agent validation to only check properties being updated (not
all required properties)
### Code Quality Improvements
- Extracted `getRecordDisplayName` utility that mirrors frontend's
`getLabelIdentifierFieldValue` logic
- Uses object metadata to determine the correct label identifier field
- Handles `FULL_NAME` composite type for person/workspaceMember objects
- Shared across create, find, and update record services
## Net Impact
- **~1,200 lines deleted** (complex routing/planning code)
- **~500 lines added** (simpler tool registry + record links)
- Significantly reduced code complexity
- Better tool discovery through full catalog in system prompt
- Improved UX with clickable record references
## Testing
- Typecheck passes
- Lint passes
- Manual testing of AI chat with record creation and linking
## Context
Deprecating TwentyORMManager in favor of TwentyORMGlobalManager
(temporarily, as this will simplify the ultimate goal to later replace
all usages with the new TwentyORMGlobalManagerV2 which will have a
similar signature)
This means this PR had to refactor a bit of code to pass down the
workspaceId when not available directly as it is now a requirement,
meaning we also deprecated scopedWorkspaceContextFactory to have a less
obscure way to fetch the workspaceId and have something more
declarative.
Step 3 will be to update TwentyORMGlobalManager to use a featureFlag
toggling and use the new GlobalWorkspaceOrmManager internally using the
new cache service
Step 4 will be to remove the feature flag and pg_pool patch
- on draft creation, do not fetch the full version. Avoid the fetch of
steps and trigger
- on activation, we were performing 8 queries/mutations synchronously +
2 additional for automated triggers. I refacto the call it it gets
reduced to 4 queries/mutations + 2 additional for automated triggers
Implements permission intersection (AND logic) to prevent permission
escalation when agents act on behalf of users.
### Changes:
- **Permission Intersection**: Operations requiring both user AND agent
permissions
- **RoleContext Type**: Unified type supporting single `roleId` or
multiple `roleIds` for intersection
- **CRUD Services**: Updated to accept `roleContext` for granular
permission control
- **Agent Integration**: Chat agents now use user + agent role
intersection for all operations
- **ORM Layer**: Enhanced `getRepository` to support multi-role
permission checks
### Related:
- Part 2 of ["Acting on behalf of user" concept
PR](https://github.com/twentyhq/twenty/pull/15103)
[Closes#1661](https://github.com/twentyhq/core-team-issues/issues/1661)
---------
Co-authored-by: Félix Malfait <felix.malfait@gmail.com>
https://github.com/user-attachments/assets/d6c565eb-9a29-4830-9396-5f979c8caa7b
- Added a new component for manual trigger (mostly duplicated from
previous one). Will remove the old one once all data are migrated
- Updated schema output so the current item of the iterator can be typed
Todo left:
- migrate old triggers
- add an util to search iterator output. Today current item fields will
be displayed as not found
- set new manual triggers for workflow runs
- replace save by insert
- if the insert output is needed, cast the generatedMaps
- remove transactions from trigger services. Doing it manually would be
complex and not reliable
Félix Malfait