## What & why
Adds an `ask_questions` tool that lets the in-app **Ask AI** assistant
**pause a turn to ask the user one or more multiple-choice questions**
(per the [Figma
design](https://www.figma.com/design/xt8O9mFeLl46C5InWwoMrN/Twenty?node-id=105959-117153))
and resume once answered — instead of guessing on
ambiguous/consequential decisions.
The tool is **harness-only**: an interactive question UI is meaningless
without a user to answer it, so it must be absent from MCP and from
head-less workflow agents.
## Design — true tool-result resume (not a synthetic user message)
The user's answer is a **structured tool result bound to the
`toolCallId`**, and the **same agent turn resumes** — exactly how
Anthropic (`tool_result` by `tool_use_id`) and OpenAI
(`function_call_output`) model human-in-the-loop.
The naive form of this (leave the tool call in `input-available` to mean
"pending") is **impossible** here: `finalizeDanglingToolParts` rewrites
`input-available` → `output-error` ("Tool execution was interrupted") on
both the persist path (`addMessage`) and the model-reload path
(`chat-execution.service.ts`). That util is a load-bearing safety net,
so weakening it is the wrong move.
Instead:
- `ask_questions` is an **inline, chat-only tool with an `execute` that
returns a `status: 'pending'` result immediately**, so the tool part is
always `output-available` and **immune to `finalizeDanglingToolParts`**.
`stopWhen(hasToolCall('ask_questions'))` halts the turn right after the
call (the model never sees the placeholder).
- A nullable **`thread.pendingQuestionMessageId`** marker records that a
turn is awaiting an answer.
- The new **`answerAgentChatQuestion`** mutation atomically *claims* the
question (clears the marker, marks the thread streaming), **writes the
answer onto the same tool part** (`status: 'answered'`), and
**re-enqueues the turn via the existing `existingTurnId` plumbing**
(`isResume` bypasses the per-turn dedup guard). On resume
`finalizeDanglingToolParts` leaves the `output-available` part untouched
and `convertToModelMessages` emits `assistant(tool_use)` +
`tool_result(answers)`, so the model continues.
This achieves the platform-aligned semantics **without** weakening the
finalize safety net or inventing a fragile new part state.
### Meets the two requirements
- **Survives refresh, scoped per-thread** — the pending state is a
normal persisted `output-available` part + the thread marker; the
frontend card is derived per-thread from the loaded messages, so it
re-appears on reload and only on its own thread.
- **Takes priority over the queue** — a unified `isBlocked =
activeStreamId || pendingQuestionMessageId` gate is applied in both
`sendChatMessage` (new messages queue) and `flushNextQueuedMessage` (the
drain). The queue cannot unpile until the question is answered and the
resumed turn completes.
### Harness-only by construction
`ask_questions` is added **only** to the chat's inline `activeTools`
(like `learn_tools`/`execute_tool`/`load_skills`). It never enters the
tool registry/catalog, so it is invisible to MCP and to workflow agents
— no `MCP_EXCLUDED_TOOL_NAMES` entry needed.
## UX
While a question is pending, the **composer is replaced by the question
card** (matching the Figma): question title + pager (`1/2`), numbered
option rows (`IconSquareNumber*`) with per-option info-icon descriptions
and a "Recommended" badge, and the normal composer as the free-text
fallback ("Type anything to do differently."). The transcript shows a
compact "Asking questions…" status line that becomes an answered
summary.
## Changes
**twenty-shared**
- `ai/types/AskQuestionsToolTypes.ts` —
`AskQuestionItem/Option/Answer/Result`, `ASK_QUESTIONS_TOOL_NAME`.
**twenty-server**
- `ai-chat/tools/ask-questions.tool.ts` — inline tool factory
(pending-result `execute`, zod schema, 1–4 questions × 2–4 options).
- `chat-execution.service.ts` — add to `activeTools` +
`preloadedToolNames`; `hasToolCall` in `stopWhen`.
- `chat-system-prompts.const.ts` — when-to-use guidance.
- `entities/agent-chat-thread.entity.ts` — `pendingQuestionMessageId`
column.
- `stream-agent-chat.job.ts` — set the marker on a question pause;
bypass the dedup guard on resume; suppress the no-text warning for
question pauses.
- `agent-chat-streaming.service.ts` — gate `flushNextQueuedMessage`;
`enqueueResumeStream`.
- `agent-chat.resolver.ts` — gate `sendChatMessage`;
`answerAgentChatQuestion` mutation.
- `agent-chat.service.ts` — `resolvePendingQuestion` (atomic claim +
write answer).
- `dtos/agent-chat-question-answer.input.ts`, `ai.exception.ts`
(`QUESTION_NOT_PENDING`), `utils/find-pending-question-part.util.ts`.
**twenty-front**
- `components/AiChatQuestionCard.tsx` — the interactive card (matches
Figma tokens) + `__stories__/AiChatQuestionCard.stories.tsx`.
- `components/AiChatEditorSection.tsx` — swap the composer for the card
while pending.
- `components/AiChatQuestionStatusRenderer.tsx` + branch in
`AiChatAssistantMessageRenderer.tsx`.
- `states/selectors/agentChatPendingQuestionComponentSelector.ts`,
`types/AgentChatPendingQuestion.ts`.
- `hooks/useSubmitQuestionAnswer.ts` + `utils/markQuestionAnswered.ts`
(optimistic) + `graphql/mutations/answerAgentChatQuestion.ts`.
A design doc lives at
`packages/twenty-server/docs/ASK_USER_QUESTION_TOOL_PLAN.md`.
## Migration
Adds a nullable `pendingQuestionMessageId` (uuid) column to
`core.agentChatThread`. Needs a generated **fast instance command**
(`database:migrate:generate --name addThreadPendingQuestion --type
fast`) — see "Verification status".
## Tests
- Server: `ask-questions.tool.spec.ts` (pending echo + schema bounds),
`find-pending-question-part.util.spec.ts`.
- Front: `markQuestionAnswered.test.ts`, plus the Storybook story.
## Verification status (please read)
This branch was authored in an environment where the monorepo `yarn
install` repeatedly failed on transient TLS resets from the package
registry, so I could **not** locally run the mechanical gates. The logic
was reviewed by hand and the `ai@6.0.97` exports used (`hasToolCall`,
`stepCountIs`, `generateId`) were confirmed against the package's type
defs. Still **TODO** (will rely on CI / a follow-up once deps install):
- [ ] `nx run twenty-shared:generateBarrels` (the `ai/index.ts` export
was added by hand; regen to reconcile)
- [ ] `nx run twenty-front:graphql:generate` (new mutation + input type)
- [ ] generate the fast instance command (migration) for the new column
- [ ] `typecheck` + `lint:diff-with-main` (front + server) — expect
minor import-ordering autofixes
- [ ] run the unit tests
**Screenshots:** reproducing the live flow needs an AI provider API key
(to get the model to actually call `ask_questions`), which isn't
available here. The card can be screenshotted from its **Storybook
story** (`AiChatQuestionCard.stories.tsx`) with no API key — I'll add
that image once deps install, or a reviewer can run `nx storybook
twenty-front`.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
https://claude.ai/code/session_01AArS8H3y3Z1Qwm763xhPLB
---
_Generated by [Claude
Code](https://claude.ai/code/session_01AArS8H3y3Z1Qwm763xhPLB)_
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Félix Malfait
4aaf171d63
