feat: v2.2.3 - Stability, Self-Reflector & Intent Alignment
- 버전 2.2.3 상향 및 PATCHNOTES.md 업데이트 - [신규] src/features/selfReflector/ - 성찰 실행/검증/프롬프트 모듈 추가 - [신규] intentAlignment.ts, intentClassifier.ts - 의도 정렬 시스템 추가 - [신규] pixelOfficeState.ts - 픽셀 오피스 상태 관리 추가 - sidebarProvider, dispatcher, chatHandlers 핵심 로직 최적화 - astra-2.2.3.vsix 패키지 생성 완료 (298 tests PASS)
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"name": "astra",
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"displayName": "Astra",
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"description": "The personal intelligence layer for Antigravity and VS Code. A private cognitive partner for deep project context, memory, and proactive strategic decision-making.",
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"version": "2.2.1",
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"version": "2.2.3",
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"publisher": "g1nation",
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"license": "MIT",
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"icon": "assets/icon.png",
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@@ -130,6 +130,10 @@
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{
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"command": "g1nation.company.openSessions",
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"title": "Astra: Open 1인 기업 Sessions Folder"
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},
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{
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"command": "g1nation.company.pixelOffice.open",
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"title": "Astra: Open Pixel Office (Full Screen)"
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}
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],
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"keybindings": [
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@@ -421,6 +425,59 @@
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"type": "boolean",
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"default": true,
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"description": "Persist substantive Reflector critiques to the active brain as lesson cards under `lessons/auto-reflector/`. Future missions automatically retrieve these cards (via the existing Experience-Memory pipeline) and inject them as ‘[⚠ ACTIVE LESSONS — verify these BEFORE finalizing]’ guardrails into Planner/Researcher/Writer context. A repeated critique (similar title) bumps `occurrences` and escalates `severity` (low→medium→high) instead of duplicating the card, so recurring patterns get louder over time. Disable to keep critiques single-mission only."
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},
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"g1nation.company.intentClassifierModel": {
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"type": "string",
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"default": "",
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"description": "Model used to classify whether an incoming chat message in 1인 기업 모드 is a (a) casual chat / question, (b) follow-up on the previous round, or (c) a brand-new task that should trigger the full work pipeline. Empty → uses g1nation.defaultModel. Pick a fast small model (e.g. gemma 4 e2b) so the classifier doesn't add latency before every chat send. The classifier runs once per user message and returns a one-token-ish JSON verdict, so even slow hardware sees minimal overhead."
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},
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"g1nation.company.disableIntentClassifier": {
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"type": "boolean",
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"default": false,
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"description": "Bypass the intent classifier and always run the full work pipeline on every chat message in 1인 기업 모드 (legacy behaviour). Enable this only if you want every input — including 'thanks', 'show me X again' — to dispatch all agents. Off by default because most chat messages aren't new work and shouldn't burn a full pipeline."
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},
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"g1nation.company.autoSelectPipeline": {
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"type": "boolean",
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"default": true,
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"description": "Let the intent classifier *automatically switch* to the pipeline it recommends for this turn (e.g. short '기획서까지만' for a planning ask, full '풀 프로덕트' for an end-to-end product). Your explicitly-activated pipeline is bypassed for the round but the activation itself isn't changed. On by default — the classifier's read of the user's intent (especially explicit signals like '기획만'·'디자인만') should be honoured. Set to false if you'd rather always run the pipeline you activated yourself."
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},
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"g1nation.company.intentAlignmentMode": {
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"type": "string",
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"enum": ["off", "smart", "strict"],
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"default": "smart",
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"description": "Intent Alignment — turn user prompts into an explicit Requirement Contract (C-G-C-F-Q) before dispatching a pipeline. 'off' = legacy, pipeline runs immediately. 'smart' (default) = run when confidence is high, else show a confirmation card; ask up to N rounds of clarifying questions if information is missing. 'strict' = always show the contract card and require user confirmation, regardless of confidence. Goal: stop agents from silently guessing at the user's mental model."
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},
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"g1nation.company.intentAlignmentMaxRounds": {
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"type": "number",
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"minimum": 1,
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"maximum": 5,
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"default": 3,
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"description": "Maximum back-and-forth rounds the Intent Alignment analyzer is allowed to ask before forcing a 'confirm or cancel' card (it stops asking new questions and shows the current contract for user approval). Each round = one LLM call. Default 3."
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},
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"g1nation.selfReflector.enabled": {
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"type": "boolean",
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"default": true,
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"description": "Self-Reflector Phase A — append a [Self-Reflector Check] block at the end of every substantive LLM answer (Consistency / Completeness / Accuracy, plus References / Paths for code answers). Zero extra LLM calls — the rule lives in the system prompt and the model self-imposes the checklist. Turns response quality up by making the verification step explicit. Disable for purely casual / chat-only usage."
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},
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"g1nation.selfReflector.externalVerification": {
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"type": "boolean",
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"default": false,
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"description": "Self-Reflector Phase B — after every 1인 기업 specialist response, run a *separate* LLM call to verify the output from an outside-context perspective (catches the 'same model self-validates' blind spot). Failed checks trigger one auto-revise round. Off by default — adds +1 LLM call per dispatched stage."
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},
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"g1nation.selfReflector.executionVerification": {
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"type": "boolean",
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"default": false,
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"description": "Self-Reflector Phase C — after a code file is created via <create_file>, automatically run the language's syntax check (Python: py_compile, JS: node --check, TS: project tsc --noEmit). Failures are surfaced in the action report so the user (and the agent on a follow-up) can see exactly what broke. Requires the language toolchain installed on the user's machine. Off by default."
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},
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"g1nation.company.pixelOffice.enabled": {
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"type": "boolean",
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"default": true,
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"description": "Show the Pixel Office visualisation panel above the chat — a small pixel-office-style display that mirrors the agent's current pipeline status (analyzing, need_clarification, executing, reviewing, waiting_approval, done, etc.) and the current task / contract / open questions. UI layer only; turning it off does not change any agent behaviour."
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},
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"g1nation.company.pixelOffice.bubbles": {
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"type": "boolean",
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"default": true,
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"description": "Show short comic-style speech bubbles above the Pixel Office character on status changes / key events (e.g. '코드 들어간다', '잠깐, 이건 다시 보자', '좋아, 끝났다!'). Bubbles are purely narrative — they never influence the agent's decisions. Disable for a quieter UI."
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}
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}
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}
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