docs: refocus README for extension consumers [skip ci]
This commit is contained in:
Erik Kotsiuba
@@ -77,224 +77,6 @@ Ask the agent to elaborate on notes before finalizing choices.
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## Use
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After installation, the package registers one tool: `ask_user`.
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That is enough for the agent to gain this clarification capability. The extension already injects prompt guidance that encourages the agent to call `ask_user` when requirements are ambiguous or user preference matters, instead of guessing.
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This package also includes an auto-bundled skill profile at `skills/ask-user/SKILL.md` (`ask-user`) for stricter decision-gate behavior in high-stakes or ambiguous boundaries. It is enabled by default when the package is installed, but can be disabled via `pi config`.
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You can still add your own agent instruction if you want to further reinforce when and how the tool should be used.
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Use `type: "preview"` only when every option includes `preview` text for a dedicated preview pane. Descriptions alone are not enough.
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### Optional extra agent instruction
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```text
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If you need clarification, prefer `ask_user` over guessing.
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Ask 1-3 concise questions.
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Use short tab labels.
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Prefer 2-4 options per question.
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Include descriptions for each option.
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Use `type: "single"` unless multiple options can genuinely apply.
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Use `type: "multi"` only when the user may need to select several answers.
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Always include a non-empty `value` for every option.
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Use `type: "preview"` only when every option includes non-empty `preview` text for the preview panel.
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After answers are returned, continue the task using those answers explicitly.
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```
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## Tool input
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`ask_user` accepts:
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```ts
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{
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title?: string,
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questions: [
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{
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id: string,
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label?: string,
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prompt: string,
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type?: "single" | "multi" | "preview",
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required?: boolean,
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options: [
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{
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value: string,
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label: string,
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description?: string,
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preview?: string
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}
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]
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}
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]
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}
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```
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### Example tool call payload
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```json
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{
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"title": "Implementation preferences",
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"questions": [
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{
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"id": "style",
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"label": "Style",
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"prompt": "How should I frame the next prompt?",
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"type": "single",
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"options": [
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{
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"value": "minimal",
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"label": "Minimal",
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"description": "A short, direct question with few options."
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},
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{
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"value": "balanced",
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"label": "Balanced",
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"description": "A standard prompt with a bit more context."
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},
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{
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"value": "rich",
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"label": "Rich",
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"description": "A more descriptive prompt with extra detail."
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}
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]
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},
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{
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"id": "frameworks",
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"label": "Frontend",
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"prompt": "Which frontend frameworks have you used?",
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"type": "multi",
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"options": [
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{ "value": "react", "label": "React", "description": "Most popular UI library" },
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{ "value": "vue", "label": "Vue", "description": "Progressive framework for building UIs" },
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{ "value": "svelte", "label": "Svelte", "description": "Compiler-based approach" }
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]
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}
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]
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}
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```
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## Returned result
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The returned result now also includes:
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```ts
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{
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error?: {
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kind: "invalid_input"
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issues: Array<{ path: string; message: string }>
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}
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mode: "submit" | "elaborate"
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continuation?: {
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strategy: "refine_only" | "resume"
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affectedQuestionIds: string[]
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preservedAnswers: Record<string, AskResultAnswer>
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questionStates: Record<string, {
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status: "answered" | "needs_clarification" | "unanswered"
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}>
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}
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elaboration?: {
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instruction: string
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nextAction: "clarify" | "clarify_then_reask"
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items: Array<
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| {
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target: { kind: "question" }
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question: {
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id: string
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label: string
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prompt: string
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type: "single" | "multi" | "preview"
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options: Array<{
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value: string
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label: string
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description?: string
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preview?: string
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}>
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}
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answered: boolean
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answer?: AskResultAnswer
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note: string
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}
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| {
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target: { kind: "option"; optionValue: string }
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question: {
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id: string
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label: string
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prompt: string
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type: "single" | "multi" | "preview"
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options: Array<{
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value: string
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label: string
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description?: string
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preview?: string
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}>
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}
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option: {
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value: string
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label: string
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description?: string
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preview?: string
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}
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selected: boolean
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answered: boolean
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answer?: AskResultAnswer
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note: string
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}
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>
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}
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}
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```
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The returned `details.answers[questionId]` object may include:
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```ts
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{
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values: string[]
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labels: string[]
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indices: number[]
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customText?: string
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note?: string
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optionNotes?: Record<string, string>
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}
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```
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Behavior details:
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- payloads are validated before the UI opens: question ids must be unique, option values must be unique within a question, and required text fields must not be blank
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- preview questions require preview text for every option; descriptions alone are not enough, and invalid preview payloads suggest adding preview text or switching to `type: "single"`
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- `required` defaults to `false` and remains advisory only
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- question-level notes are submitted whenever authored
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- option notes can be authored for any active option during the UI flow
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- only notes for currently selected options are included in the submitted result
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- deselecting an option keeps its note in UI state, so re-selecting it restores the note
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- empty note text clears the note
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- on single-select questions, saving a free-form answer replaces selected options for that question
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- on multi-select questions, saving a free-form answer keeps other selected options intact
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- on multi-select questions, submitted `values` and `labels` keep selected options first and append the free-form answer last when both exist
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- invalid payloads return `details.error.kind === "invalid_input"` with structured `issues` and a transcript-friendly `Invalid ask_user payload:` message
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- unanswered questions are omitted from `details.answers`
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- in elaborate mode, `details.answers` contains only committed answers; note-only entries move into `details.elaboration.items`
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- `details.continuation.strategy === "refine_only"` means the next ask should refine the current flow instead of restarting it
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- `details.continuation.preservedAnswers` contains prior answers that should be carried forward without re-asking
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- `details.continuation.affectedQuestionIds` lists the only questions that should be revisited
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- `details.continuation.questionStates` marks each question as `answered`, `needs_clarification`, or `unanswered`
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- submit review tab now offers `Submit`, `Elaborate`, and `Cancel`
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- while `Submit` or `Cancel` is highlighted on the review tab, notes are previewed only for questions with selected answers
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- while `Elaborate` is highlighted on the review tab, the preview expands to show all question notes and all option notes, including notes on unselected options
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- choosing `Elaborate` finishes immediately and returns `mode: "elaborate"`
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- `details.elaboration.items` includes all question notes and all option notes, even for unselected options
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- every elaboration item carries the full normalized question and option list for that question, so the agent can resolve referential notes like `above` without relying on chat memory alone
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- `details.elaboration.instruction` explicitly tells the agent to answer the clarification directly first, then re-ask only the affected questions if needed
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- after clarification, agents should prefer another structured follow-up over plain-text multiple choice if a decision is still unresolved
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- once prior answers narrow the branch, agents should bundle the next 2-3 related unresolved decisions into one follow-up ask when possible instead of asking a long chain of one-question follow-ups
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- elaborate summary/result text now emits direct note-specific lines such as `User asked to elaborate on question "Which option would you like to select?" option "Option A" with note "why this one?"`
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- free-form answer editors support pi-style `@` file path autocomplete for quickly mentioning project files
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- keyboard interactions for navigation, editing, review actions, and cancellation are listed in [Key bindings](#key-bindings) below
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---
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## Key bindings
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| Key | Context | Effect |
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@@ -319,9 +101,17 @@ Behavior details:
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| `Tab` `Shift+Tab` / `←` `→` | Empty editor | Switch tabs without closing editor |
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| Arrow keys / `Tab` | Non-empty editor | Stay in editor for cursor movement |
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---
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## Use
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If pi runs without UI, `ask_user` returns a `Needs user input` message plus normalized pending questions in `details.questions` so a caller can re-ask them manually.
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After installation, the extension registers the `ask_user` tool.
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Agents can auto-discover and call it when they need clarification instead of guessing. In interactive sessions, it opens a terminal UI flow for structured answers and returns normalized answers back to the agent.
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This package also bundles the `ask-user` skill profile from `skills/ask-user/SKILL.md`. It reinforces when to use the tool, is enabled by default when installed, and can be disabled via `pi config`. The skill was inspired by https://github.com/edlsh/pi-ask-user.
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You can still add your own agent instruction if you want to further reinforce usage.
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For exact input/output and UX guarantees, see [`docs/contract.md`](docs/contract.md).
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## Local development
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