From c4f01fd6af09ff5d03411c2804cd77169d322f06 Mon Sep 17 00:00:00 2001 From: g1nation Date: Sat, 16 May 2026 13:18:49 +0900 Subject: [PATCH] v2.2.13: Pixel Office Interactive Editor & Core Refinement --- .astra/project-context/architecture.md | 60 +- .astra/project-context/scan-cache.json | 1118 ++++++++--------- ...d46d2ca2057b05c488be1dcf439166ac5a9a1.json | 2 +- ...9f4f39d2bc368f77456c37b5eef9a94a66b5c.json | 2 +- ...5c7a44d7661af673b24e3f49551a7a2e50280.json | 2 +- ...adc543795e4b427b64540a49c9ab27c7fe213.json | 4 +- ...son => stress_conflict_1778902731247.json} | 22 +- PATCHNOTES.md | 11 + docs/records/ConnectAI/chronicle.config.json | 10 +- package.json | 2 +- src/sidebarProvider.ts | 452 ++++++- 11 files changed, 1030 insertions(+), 655 deletions(-) rename .astra/tests/stress/.astra/missions/{stress_conflict_1778845577925.json => stress_conflict_1778902731247.json} (78%) diff --git a/.astra/project-context/architecture.md b/.astra/project-context/architecture.md index cf5df64..ce02838 100644 --- a/.astra/project-context/architecture.md +++ b/.astra/project-context/architecture.md @@ -3,20 +3,20 @@ ## Snapshot -- **Workspace**: `connectai` `v2.2.11` _(absolute path varies by environment; resolved from the active VS Code workspace)_ +- **Workspace**: `ConnectAI` `v2.2.12` _(absolute path varies by environment; resolved from the active VS Code workspace)_ - **Description**: The personal intelligence layer for Antigravity and VS Code. A private cognitive partner for deep project context, memory, and proactive strategic decision-making. - **Stack**: TypeScript, Node.js, VS Code Extension, LM Studio SDK, Test runner -- **Stats**: 224 source files, ~45,895 lines across 5 top-level modules. +- **Stats**: 224 source files, ~45,925 lines across 5 top-level modules. ## Last Refresh -- **Time**: 2026-05-15T11:45:54.886Z -- **Files newly analysed**: 2 -- **Files reused from cache**: 222 +- **Time**: 2026-05-16T03:37:49.405Z +- **Files newly analysed**: 0 +- **Files reused from cache**: 224 ## Directory Map ```mermaid mindmap - root((connectai)) + root((ConnectAI)) src/ features/ core/ @@ -64,14 +64,14 @@ flowchart LR ## Modules -### `src/` — 110 files, ~30,899 lines +### `src/` — 110 files, ~30,926 lines **Sub-directories** - `src/features/` (37) — 기본 에이전트 로스터 — 1인 기업 모드의 출고 디폴트. 설계 의도: 소프트웨어/게임 개발 IT 회사의 1인 기업 운영을 가정. 한 사람이 기획 → 디자인 → 개발 → QA → 출시 → 운영/마케팅을 모두 책임질 때 - `src/core/` (15) — Astra Path Resolver (경로 해결기) Astra의 모든 데이터 파일(.astra 디렉토리)의 경로를 중앙에서 관리합니다. 확장 프로그램의 설치 경로(extensionUri) 기반으로 .astra 디렉토 - `src/memory/` (8) — Episodic Memory (일화 기억) 과거 대화/회의/결정의 맥락 흐름을 저장합니다. 세션 종료 시 자동으로 에피소드를 요약하여 저장합니다. "왜 이렇게 결정했는지", "어떤 흐름으로 진행했는지" 기록. 저장 - `src/retrieval/` (8) — Brain Index — persistent, mtime-keyed tokenized cache of the Second Brain RAG 검색은 매 질의마다 브레인의 모든 .md 파일을 읽고 토크나이즈해서 TF-I -- `src/docs/` (6) — Bug: Edited agent.ts Edited agent.ts Edited agent.ts Edited agent.ts Edited agent.ts ... +- `src/docs/` (6) — src Chronicle Records - `src/lib/` (6) — Context Manager (컨텍스트 한계 관리) "context length = 132k" 는 "답변을 132k 토큰까지 생성해도 된다" 가 아닙니다. 시스템 프롬프트 + 대화 기록 + 입력 문서 + 생성될 답변 - `src/integrations/` (4) — Per-chat conversation history for the Telegram bot. Why this exists: the previous bot was stateless — every inbound mess - `src/lmstudio/` (4) — 4 files (.ts) @@ -87,12 +87,12 @@ flowchart LR - `src/core/services.ts` (164 lines) - `src/lib/paths.ts` (151 lines) - `src/features/company/companyConfig.ts` (896 lines) — State + config plumbing for 1인 기업 모드. Two surfaces: - CompanyState (runtime data: enabled flag, company name, which agents are active, per-agent model overrides). Persisted in VS Code's globalState so -- `src/sidebarProvider.ts` (5083 lines) +- `src/sidebarProvider.ts` (5119 lines) - `src/memory/types.ts` (126 lines) — Memory Type Definitions (메모리 타입 정의) Astra의 5-Layer Cognitive Memory System의 모든 타입을 정의합니다. ① Short-Term ② Long-Term ③ Project ④ Procedural ⑤ Episodic - `src/retrieval/scoring.ts` (518 lines) — Scoring Engine — TF-IDF + Bilingual Tokenizer 단순 includes() 키워드 매칭을 넘어서, TF-IDF 가중치 기반의 문서 스코어링을 제공합니다. 한국어/영어 양국어 토크나이저를 포함합니다. - `src/skills/agentKnowledgeMap.ts` (374 lines) - `src/retrieval/lessonHelpers.ts` (325 lines) — Lesson / Experience Memory — pure helpers (no vscode dependency) "Lesson" = a markdown file in the active brain that captures a past mistake/risk and how to avoid repeating it. Identified by a lessons -- `src/agent.ts` (3269 lines) +- `src/agent.ts` (3260 lines) - `src/lib/engine.ts` (906 lines) - `src/features/company/dispatcher.ts` (1419 lines) — Sequential dispatcher for 1인 기업 모드. Drives one company "turn": user prompt → CEO planner (JSON {brief, tasks}) → for each task in plan: dispatch one specialist (sequentially) - build specialist prompt - `src/features/approval/approvalQueue.ts` (129 lines) @@ -107,11 +107,11 @@ flowchart LR - `src/features/company/intentAlignment.ts` (334 lines) — Intent Alignment — 사용자의 자연어 요청을 실행 가능한 작업 조건으로 변환. 사용자는 자기 의도와 배경지식이 에이전트에게 충분히 전달되었다고 착각하는 경향이 있다 (투명성의 착각·지식의 저주·공통 기반 부족). 그래서 에이전트가 즉시 작업에 돌입하면 사용자가 머릿속에 가진 것과 다른 결과를 만들어 낸다. 이 모듈은 그 격차를 메꾸는 한 단계 - `src/features/projectChronicle/types.ts` (118 lines) -### `media/` — 6 files, ~6,763 lines +### `media/` — 6 files, ~6,766 lines **Key files** -- `media/sidebar.css` (1990 lines) — Stylesheet -- `media/sidebar.js` (3598 lines) +- `media/sidebar.css` (1986 lines) — Stylesheet +- `media/sidebar.js` (3605 lines) - `media/sidebar.html` (531 lines) — Astra - `media/settings-panel.css` (210 lines) — Stylesheet - `media/settings-panel.html` (164 lines) — Astra Settings @@ -163,8 +163,8 @@ flowchart LR ### `docs/` — 75 files, ~2,886 lines **Sub-directories** -- `docs/records/` (63) — Bug: /Volumes/Data/project/Antigravity/ConnectAI 프로젝트 코드 리뷰 해줄 수 있어? 개선할 부분이 있는지, 그러고... -- `docs/docs/` (5) — Bug: Viewed integrationretrieval.test.ts:1-59 integrationretrieval.test.ts를 통해 ... +- `docs/records/` (63) — Astra Project Chronicle Records +- `docs/docs/` (5) — docs Chronicle Records **Key files** - `docs/TELEGRAM_REMOTE_EXECUTION_PLAN.md` (452 lines) — Telegram Remote Execution 기획서 @@ -174,24 +174,24 @@ flowchart LR - `docs/records/ConnectAI/development/2026-05-03_connectai_project_knowledge_overview.md` (121 lines) — Astra Project Knowledge Overview - `docs/records/ConnectAI/timeline.md` (140 lines) — Project Timeline - `docs/Advanced_Features_Implementation_Guide.md` (40 lines) — Advanced Features Implementation Guide +- `docs/PROJECT_CHRONICLE_GUARD_ROADMAP.md` (43 lines) — Project Chronicle Guard: Search Engine Roadmap +- `docs/UX_UI_Consistency_Guidelines.md` (44 lines) — UX/UI Consistency Guidelines +- `docs/docs/records/docs/README.md` (18 lines) — docs Chronicle Records - `docs/docs/records/docs/bugs/BUG-0001-viewed-integration-retrieval-test-ts-1-59-integration-retrie.md` (16 lines) — Bug: Viewed integrationretrieval.test.ts:1-59 integrationretrieval.test.ts를 통해 ... - `docs/docs/records/docs/chronicle.config.json` (11 lines) — JSON configuration - `docs/docs/records/docs/project-profile.md` (31 lines) — Project Profile -- `docs/docs/records/docs/README.md` (18 lines) — docs Chronicle Records - `docs/docs/records/docs/timeline.md` (7 lines) — Project Timeline -- `docs/PROJECT_CHRONICLE_GUARD_ROADMAP.md` (43 lines) — Project Chronicle Guard: Search Engine Roadmap -- `docs/records/ConnectAI/bugs/BUG-0001-volumes-data-project-antigravity-connectai-프로젝트-코드-리뷰-해줄-수-있.md` (16 lines) — Bug: /Volumes/Data/project/Antigravity/ConnectAI 프로젝트 코드 리뷰 해줄 수 있어? 개선할 부분이 있는지, 그러고... -- `docs/records/ConnectAI/bugs/BUG-0002-지금-내가-분석-요청하고-너가-답을-줄때-아래-템플릿에-맞춰-답을-써주고-있는데-개선-포인트가-있는지-확인해.md` (16 lines) — Bug: 지금 내가 분석 요청하고 너가 답을 줄때 아래 템플릿에 맞춰 답을 써주고 있는데, 개선 포인트가 있는지 확인해줘. ## 내가 보는 위험 가장 큰... -- `docs/records/ConnectAI/bugs/BUG-0003-volumes-data-project-antigravity-connectai-내-질문에-대한-답변이-잘-정리.md` (16 lines) — Bug: /Volumes/Data/project/Antigravity/ConnectAI 내 질문에 대한 답변이 잘 정리되서 알려주긴 하는데 focused... -- `docs/records/ConnectAI/bugs/BUG-0004-volumes-data-project-antigravity-connectai-내-질문에-대한-답변이-잘-정리.md` (16 lines) — Bug: /Volumes/Data/project/Antigravity/ConnectAI 내 질문에 대한 답변이 잘 정리되서 알려주긴 하는데 focused... -- `docs/records/ConnectAI/bugs/BUG-0005-다시한번-답줘-volumes-data-project-antigravity-connectai-내-질문에-대한-.md` (16 lines) — Bug: 다시한번 답줘. /Volumes/Data/project/Antigravity/ConnectAI 내 질문에 대한 답변이 잘 정리되서 알려주긴 하는... -- `docs/records/ConnectAI/bugs/BUG-0006-volumes-data-project-antigravity-connectai-내-질문에-대한-답변이-잘-정리.md` (16 lines) — Bug: /Volumes/Data/project/Antigravity/ConnectAI 내 질문에 대한 답변이 잘 정리되서 알려주긴 하는데 focused... -- `docs/records/ConnectAI/bugs/BUG-0007-volumes-data-project-antigravity-connectai-내-질문에-대한-답변이-잘-정리.md` (16 lines) — Bug: /Volumes/Data/project/Antigravity/ConnectAI 내 질문에 대한 답변이 잘 정리되서 알려주긴 하는데 focused... -- `docs/records/ConnectAI/bugs/BUG-0008-volumes-data-project-antigravity-connectai-내-질문에-대한-답변이-잘-정리.md` (16 lines) — Bug: /Volumes/Data/project/Antigravity/ConnectAI 내 질문에 대한 답변이 잘 정리되서 알려주긴 하는데 focused... -- `docs/records/ConnectAI/bugs/BUG-0009-문제점을-읽고-어떻게-개선하는게-최선인지-분석해주면-좋겠어-알겠습니다-지금부터-connectai-프로젝트-에.md` (16 lines) — Bug: 문제점을 읽고 어떻게 개선하는게 최선인지 분석해주면 좋겠어. 알겠습니다. 지금부터 ConnectAI 프로젝트에만 완전히 집중하겠습니다. ... -- `docs/records/ConnectAI/bugs/BUG-0010-문제점을-읽고-어떻게-개선하는게-최선인지-분석해주면-좋겠어-알겠습니다-지금부터-connectai-프로젝트-에.md` (16 lines) — Bug: 문제점을 읽고 어떻게 개선하는게 최선인지 분석해주면 좋겠어. 알겠습니다. 지금부터 ConnectAI 프로젝트에만 완전히 집중하겠습니다. ... -- `docs/records/ConnectAI/bugs/BUG-0011-문제점을-읽고-어떻게-개선하는게-최선인지-분석해주면-좋겠어-알겠습니다-지금부터-connectai-프로젝트-에.md` (16 lines) — Bug: 문제점을 읽고 어떻게 개선하는게 최선인지 분석해주면 좋겠어. 알겠습니다. 지금부터 ConnectAI 프로젝트에만 완전히 집중하겠습니다. ... -- `docs/records/ConnectAI/bugs/BUG-0012-질문이-있어-논문을-쓰려고해-논문-주제는-서비스적이-아닌-사용자가-ai에게-구조로-질문을-해야-사용자의-의도.md` (16 lines) — Bug: 질문이 있어. 논문을 쓰려고해. 논문 주제는 서비스적이 아닌 사용자가 ai에게 구조로 질문을 해야 사용자의 의도에 맞는 답변을 받을 수 있을까야... +- `docs/records/ConnectAI/README.md` (18 lines) — Astra Project Chronicle Records +- `docs/records/ConnectAI/bugs/BUG-0001-volumes-data-project-antigravity-connectai-프로젝트-코드-리뷰-해줄-수-있.md` (16 lines) — Bug: /Volumes/Data/project/Antigravity/ConnectAI 프로젝트 코드 리뷰 해줄 수 있어? 개선할 부분이 있는지, 그러고... +- `docs/records/ConnectAI/bugs/BUG-0002-지금-내가-분석-요청하고-너가-답을-줄때-아래-템플릿에-맞춰-답을-써주고-있는데-개선-포인트가-있는지-확인해.md` (16 lines) — Bug: 지금 내가 분석 요청하고 너가 답을 줄때 아래 템플릿에 맞춰 답을 써주고 있는데, 개선 포인트가 있는지 확인해줘. ## 내가 보는 위험 가장 큰... +- `docs/records/ConnectAI/bugs/BUG-0003-volumes-data-project-antigravity-connectai-내-질문에-대한-답변이-잘-정리.md` (16 lines) — Bug: /Volumes/Data/project/Antigravity/ConnectAI 내 질문에 대한 답변이 잘 정리되서 알려주긴 하는데 focused... +- `docs/records/ConnectAI/bugs/BUG-0004-volumes-data-project-antigravity-connectai-내-질문에-대한-답변이-잘-정리.md` (16 lines) — Bug: /Volumes/Data/project/Antigravity/ConnectAI 내 질문에 대한 답변이 잘 정리되서 알려주긴 하는데 focused... +- `docs/records/ConnectAI/bugs/BUG-0005-다시한번-답줘-volumes-data-project-antigravity-connectai-내-질문에-대한-.md` (16 lines) — Bug: 다시한번 답줘. /Volumes/Data/project/Antigravity/ConnectAI 내 질문에 대한 답변이 잘 정리되서 알려주긴 하는... +- `docs/records/ConnectAI/bugs/BUG-0006-volumes-data-project-antigravity-connectai-내-질문에-대한-답변이-잘-정리.md` (16 lines) — Bug: /Volumes/Data/project/Antigravity/ConnectAI 내 질문에 대한 답변이 잘 정리되서 알려주긴 하는데 focused... +- `docs/records/ConnectAI/bugs/BUG-0007-volumes-data-project-antigravity-connectai-내-질문에-대한-답변이-잘-정리.md` (16 lines) — Bug: /Volumes/Data/project/Antigravity/ConnectAI 내 질문에 대한 답변이 잘 정리되서 알려주긴 하는데 focused... +- `docs/records/ConnectAI/bugs/BUG-0008-volumes-data-project-antigravity-connectai-내-질문에-대한-답변이-잘-정리.md` (16 lines) — Bug: /Volumes/Data/project/Antigravity/ConnectAI 내 질문에 대한 답변이 잘 정리되서 알려주긴 하는데 focused... +- `docs/records/ConnectAI/bugs/BUG-0009-문제점을-읽고-어떻게-개선하는게-최선인지-분석해주면-좋겠어-알겠습니다-지금부터-connectai-프로젝트-에.md` (16 lines) — Bug: 문제점을 읽고 어떻게 개선하는게 최선인지 분석해주면 좋겠어. 알겠습니다. 지금부터 ConnectAI 프로젝트에만 완전히 집중하겠습니다. ... +- `docs/records/ConnectAI/bugs/BUG-0010-문제점을-읽고-어떻게-개선하는게-최선인지-분석해주면-좋겠어-알겠습니다-지금부터-connectai-프로젝트-에.md` (16 lines) — Bug: 문제점을 읽고 어떻게 개선하는게 최선인지 분석해주면 좋겠어. 알겠습니다. 지금부터 ConnectAI 프로젝트에만 완전히 집중하겠습니다. ... ## VS Code Extension Surface - **Extension ID**: `g1nation.astra` @@ -319,7 +319,7 @@ Astra는 대표님의 명시적인 승인 하에 로컬 시스템의 강력한 **Designed for High-Performance Decision Making.** Copyright (C) **g1nation**. All rights reserved. -_Last auto-scan: 2026-05-15T11:45:54.886Z · signature `ac525c98`_ +_Last auto-scan: 2026-05-16T03:37:49.405Z · signature `2e3db319`_ ## Purpose diff --git a/.astra/project-context/scan-cache.json b/.astra/project-context/scan-cache.json index a993c72..7e1017d 100644 --- a/.astra/project-context/scan-cache.json +++ b/.astra/project-context/scan-cache.json @@ -1,11 +1,11 @@ { "version": 1, - "generatedAt": "2026-05-15T11:45:54.912Z", + "generatedAt": "2026-05-16T03:37:49.410Z", "files": { "src/agent.ts": { - "mtimeMs": 1778821287514.7053, - "size": 190781, - "lines": 3269, + "mtimeMs": 1778902489000, + "size": 187410, + "lines": 3260, "role": "", "imports": [ "src/utils", @@ -38,8 +38,8 @@ ] }, "src/agents/AgentWorkflowManager.ts": { - "mtimeMs": 1778720117490.4294, - "size": 2322, + "mtimeMs": 1778690404000, + "size": 2262, "lines": 60, "role": "", "imports": [ @@ -49,8 +49,8 @@ ] }, "src/agents/factory.ts": { - "mtimeMs": 1778720117507.1616, - "size": 11242, + "mtimeMs": 1778690336000, + "size": 11023, "lines": 219, "role": "", "imports": [ @@ -59,8 +59,8 @@ ] }, "src/agents/reflectionPersister.ts": { - "mtimeMs": 1778807413489.8743, - "size": 12294, + "mtimeMs": 1778763469000, + "size": 11986, "lines": 308, "role": "Reflection → Lesson persistence Take the Reflector agent's structured critique and persist any substantive findings as a lesson card in /lessons/auto-reflector/. The existing brain retrieval", "imports": [ @@ -69,8 +69,8 @@ ] }, "src/bridge.ts": { - "mtimeMs": 1778549008895.9155, - "size": 9932, + "mtimeMs": 1778681774000, + "size": 9705, "lines": 227, "role": "", "imports": [ @@ -82,21 +82,21 @@ ] }, "src/config.ts": { - "mtimeMs": 1778820338139.1692, - "size": 14921, + "mtimeMs": 1778902489000, + "size": 14623, "lines": 298, "role": "", "imports": [] }, "src/core/astraPath.ts": { - "mtimeMs": 1778037123135.2776, - "size": 1832, + "mtimeMs": 1778169995000, + "size": 1782, "lines": 50, "role": "Astra Path Resolver (경로 해결기) Astra의 모든 데이터 파일(.astra 디렉토리)의 경로를 중앙에서 관리합니다. 확장 프로그램의 설치 경로(extensionUri) 기반으로 .astra 디렉토리를 해결하여, 사용자 프로젝트 루트가 아닌 ConnectAI 패키지 내부에 데이터를 저장합니다. 이 모듈은 AAL(Astra Autonomou", "imports": [] }, "src/core/conflict.ts": { - "mtimeMs": 1778038174478.8147, + "mtimeMs": 1778169995000, "size": 1726, "lines": 30, "role": "", @@ -105,35 +105,35 @@ ] }, "src/core/dataProcessor.ts": { - "mtimeMs": 1778038193232.0127, + "mtimeMs": 1778169995000, "size": 3235, "lines": 96, "role": "Aggregate result type definition", "imports": [] }, "src/core/errorHandler.ts": { - "mtimeMs": 1777511752606.2458, - "size": 2354, + "mtimeMs": 1777808065000, + "size": 2305, "lines": 49, "role": "", "imports": [] }, "src/core/errors.ts": { - "mtimeMs": 1778037081022.028, - "size": 958, + "mtimeMs": 1778169995000, + "size": 924, "lines": 34, "role": "g1nation Custom Error Classes", "imports": [] }, "src/core/events.ts": { - "mtimeMs": 1778028987396.9893, - "size": 1028, + "mtimeMs": 1777808065000, + "size": 993, "lines": 35, "role": "", "imports": [] }, "src/core/health.ts": { - "mtimeMs": 1778038139567.3984, + "mtimeMs": 1778169995000, "size": 2873, "lines": 79, "role": "", @@ -143,7 +143,7 @@ ] }, "src/core/lock.ts": { - "mtimeMs": 1778038157826.973, + "mtimeMs": 1778169995000, "size": 2358, "lines": 66, "role": "", @@ -152,8 +152,8 @@ ] }, "src/core/queue.ts": { - "mtimeMs": 1778666871393.5244, - "size": 2509, + "mtimeMs": 1778674336000, + "size": 2428, "lines": 81, "role": "", "imports": [ @@ -161,8 +161,8 @@ ] }, "src/core/responseRecovery.ts": { - "mtimeMs": 1778664139958.9634, - "size": 12529, + "mtimeMs": 1778598587000, + "size": 12304, "lines": 225, "role": "Response Recovery — Thought Quarantine + Final-only Retry + Auto-Continuation The user already asked their question; they're waiting for an answer, not for a chance to babysit the generation engine. S", "imports": [ @@ -170,8 +170,8 @@ ] }, "src/core/services.ts": { - "mtimeMs": 1778549008895.9155, - "size": 6856, + "mtimeMs": 1778421200000, + "size": 6692, "lines": 164, "role": "", "imports": [ @@ -180,8 +180,8 @@ ] }, "src/core/session.ts": { - "mtimeMs": 1777511752609.8882, - "size": 2873, + "mtimeMs": 1777808065000, + "size": 2785, "lines": 88, "role": "", "imports": [ @@ -190,14 +190,14 @@ ] }, "src/core/statusBar.ts": { - "mtimeMs": 1778028987401.3042, - "size": 2057, + "mtimeMs": 1777808065000, + "size": 2000, "lines": 57, "role": "", "imports": [] }, "src/core/telemetry.ts": { - "mtimeMs": 1778666901466.1726, + "mtimeMs": 1778674336000, "size": 5442, "lines": 129, "role": "Telemetry — append-only usage events to .astra/usage.jsonl Why local-file telemetry instead of a webview dashboard or remote endpoint: - Astra is local-first. No data leaves the machine. - JSONL is tr", @@ -207,8 +207,8 @@ ] }, "src/core/transaction.ts": { - "mtimeMs": 1778549008897.4194, - "size": 4590, + "mtimeMs": 1778251556000, + "size": 4458, "lines": 132, "role": "", "imports": [ @@ -216,51 +216,51 @@ "src/utils" ] }, + "src/docs/records/src/README.md": { + "mtimeMs": 1777949473000, + "size": 422, + "lines": 18, + "role": "src Chronicle Records", + "imports": [] + }, "src/docs/records/src/bugs/BUG-0001-edited-agent-ts-edited-agent-ts-edited-agent-ts-edited-agent.md": { - "mtimeMs": 1778028987403.465, - "size": 1813, + "mtimeMs": 1777949473000, + "size": 1797, "lines": 16, "role": "Bug: Edited agent.ts Edited agent.ts Edited agent.ts Edited agent.ts Edited agent.ts ...", "imports": [] }, - "src/docs/records/src/bugs/BUG-0002-viewed-agent-ts-2159-2206-제공해주신-세부-파일-구조와-지식-수집-워크플로우-관점의-코드.md": { - "mtimeMs": 1778028987403.9697, - "size": 2217, + "src/docs/records/src/bugs/BUG-0002-viewed-agent-ts-2159-2206-제공해주신-세부-파일-구조와-지식-수집-워크플로우-관점의-코드.md": { + "mtimeMs": 1777949638000, + "size": 2201, "lines": 16, "role": "Bug: Viewed agent.ts:2159-2206 제공해주신 세부 파일 구조와 지식 수집 워크플로우 관점의 코드리뷰 요청을 정독했습니다. 이...", "imports": [] }, "src/docs/records/src/chronicle.config.json": { - "mtimeMs": 1778028987403.9697, - "size": 528, + "mtimeMs": 1777949638000, + "size": 517, "lines": 11, "role": "JSON configuration", "imports": [] }, "src/docs/records/src/project-profile.md": { - "mtimeMs": 1778028987404.973, - "size": 613, + "mtimeMs": 1777949473000, + "size": 582, "lines": 31, "role": "Project Profile", "imports": [] }, - "src/docs/records/src/README.md": { - "mtimeMs": 1778028987402.338, - "size": 440, - "lines": 18, - "role": "src Chronicle Records", - "imports": [] - }, "src/docs/records/src/timeline.md": { - "mtimeMs": 1778028987405.4775, - "size": 391, + "mtimeMs": 1777949638000, + "size": 381, "lines": 10, "role": "Project Timeline", "imports": [] }, "src/extension.ts": { - "mtimeMs": 1778819737212.6252, - "size": 51910, + "mtimeMs": 1778902489000, + "size": 50938, "lines": 972, "role": "", "imports": [ @@ -294,8 +294,8 @@ ] }, "src/features/approval/approvalPanelProvider.ts": { - "mtimeMs": 1778664480470.9922, - "size": 7285, + "mtimeMs": 1778674336000, + "size": 7132, "lines": 153, "role": "", "imports": [ @@ -304,8 +304,8 @@ ] }, "src/features/approval/approvalQueue.ts": { - "mtimeMs": 1778549008899.4456, - "size": 4851, + "mtimeMs": 1778251548000, + "size": 4722, "lines": 129, "role": "", "imports": [ @@ -313,8 +313,8 @@ ] }, "src/features/approval/approvalStatusBar.ts": { - "mtimeMs": 1778549008899.4456, - "size": 1642, + "mtimeMs": 1778251623000, + "size": 1601, "lines": 41, "role": "", "imports": [ @@ -322,8 +322,8 @@ ] }, "src/features/company/agents.ts": { - "mtimeMs": 1778807413492.3777, - "size": 13979, + "mtimeMs": 1778765657000, + "size": 13783, "lines": 196, "role": "기본 에이전트 로스터 — 1인 기업 모드의 출고 디폴트. 설계 의도: 소프트웨어/게임 개발 IT 회사의 1인 기업 운영을 가정. 한 사람이 기획 → 디자인 → 개발 → QA → 출시 → 운영/마케팅을 모두 책임질 때 필요한 직군을 빠짐없이 커버하되 역할이 겹치지 않게 분리한다. 직군 구분 (혼동 방지): - 기획자(business) : 무엇을 만들지 정의 ", "imports": [ @@ -331,8 +331,8 @@ ] }, "src/features/company/ceoPlanner.ts": { - "mtimeMs": 1778814432469.254, - "size": 12050, + "mtimeMs": 1778902489000, + "size": 11781, "lines": 269, "role": "CEO planner — turns a user prompt into a CompanyTaskPlan. Lifecycle of one planner call: 1. Build the planner system prompt (template + active-agent list). 2. Hit the AI service with the user prompt a", "imports": [ @@ -345,8 +345,8 @@ ] }, "src/features/company/ceoReporter.ts": { - "mtimeMs": 1778739926808.2551, - "size": 5017, + "mtimeMs": 1778762677000, + "size": 4895, "lines": 122, "role": "CEO synthesis pass — runs after all specialists have finished. Given the per-agent outputs, this asks the CEO model to produce the final markdown report (✅ 완료 / 🚀 다음 / 💡 인사이트) that the user actually", "imports": [ @@ -358,8 +358,8 @@ ] }, "src/features/company/companyConfig.ts": { - "mtimeMs": 1778811673797.1216, - "size": 41035, + "mtimeMs": 1778902489000, + "size": 40139, "lines": 896, "role": "State + config plumbing for 1인 기업 모드. Two surfaces: - CompanyState (runtime data: enabled flag, company name, which agents are active, per-agent model overrides). Persisted in VS Code's globalState so", "imports": [ @@ -368,8 +368,8 @@ ] }, "src/features/company/dispatcher.ts": { - "mtimeMs": 1778821270733.2605, - "size": 73540, + "mtimeMs": 1778902489000, + "size": 72121, "lines": 1419, "role": "Sequential dispatcher for 1인 기업 모드. Drives one company \"turn\": user prompt → CEO planner (JSON {brief, tasks}) → for each task in plan: dispatch one specialist (sequentially) - build specialist prompt", "imports": [ @@ -394,8 +394,8 @@ ] }, "src/features/company/index.ts": { - "mtimeMs": 1778814836698.1172, - "size": 2702, + "mtimeMs": 1778902489000, + "size": 2596, "lines": 106, "role": "Public API for 1인 기업 모드. Consumers (sidebarProvider, chatHandlers, command handlers) import from this barrel so internal layout can move around without touching every call site.", "imports": [ @@ -412,7 +412,7 @@ ] }, "src/features/company/intentAlignment.ts": { - "mtimeMs": 1778813958976.1824, + "mtimeMs": 1778902489000, "size": 15285, "lines": 334, "role": "Intent Alignment — 사용자의 자연어 요청을 실행 가능한 작업 조건으로 변환. 사용자는 자기 의도와 배경지식이 에이전트에게 충분히 전달되었다고 착각하는 경향이 있다 (투명성의 착각·지식의 저주·공통 기반 부족). 그래서 에이전트가 즉시 작업에 돌입하면 사용자가 머릿속에 가진 것과 다른 결과를 만들어 낸다. 이 모듈은 그 격차를 메꾸는 한 단계 ", @@ -423,7 +423,7 @@ ] }, "src/features/company/intentClassifier.ts": { - "mtimeMs": 1778819562785.657, + "mtimeMs": 1778902489000, "size": 17372, "lines": 348, "role": "Intent classifier for 1인 기업 모드 chat input. The company mode used to route every chat message through the full dispatcher (CEO planner → specialists → CEO synthesis). That meant casual messages like \"고", @@ -433,7 +433,7 @@ ] }, "src/features/company/pipelineTemplates.ts": { - "mtimeMs": 1778811940057.931, + "mtimeMs": 1778902489000, "size": 13681, "lines": 250, "role": "Built-in pipeline templates for 1인 기업 모드. These are blueprints, not data — they're surfaced in the manage panel's \"템플릿에서 추가\" dropdown so a non-developer user can stamp out a working pipeline in one cl", @@ -442,22 +442,22 @@ ] }, "src/features/company/pixelOfficeState.ts": { - "mtimeMs": 1778843402595.067, + "mtimeMs": 1778902489000, "size": 10025, "lines": 286, "role": "Pixel Office — Agent Work Pipeline 상태를 시각화하는 UI Layer 전용 모듈. ─────────────────── 설계 원칙 ─────────────────── 1. Agent 핵심 판단 로직을 절대 바꾸지 않는다. Pipeline 진행, contract 합의, 검수 cycle, 승인 게이트 — 모두 기존 dispatcher ", "imports": [] }, "src/features/company/promptAssets.ts": { - "mtimeMs": 1778720117525.2087, - "size": 6896, + "mtimeMs": 1778680887000, + "size": 6782, "lines": 114, "role": "Inlined prompt assets for the 1인 기업 mode. The CEO planner / reporter / casual-chat prompts are kept as TS string constants rather than loaded from prompts/.md at runtime, for two reasons: 1. Bundling.", "imports": [] }, "src/features/company/promptBuilder.ts": { - "mtimeMs": 1778820392456.6843, - "size": 14759, + "mtimeMs": 1778902489000, + "size": 14499, "lines": 260, "role": "System-prompt construction for company-mode agents. Each specialist needs a prompt that includes: - Their identity (name, role, specialty) + optional persona. - The action-tag contract (, ", "imports": [ @@ -469,29 +469,29 @@ ] }, "src/features/company/prompts/ceo-chat.md": { - "mtimeMs": 1778720117527.2378, - "size": 466, + "mtimeMs": 1778680831000, + "size": 462, "lines": 4, "role": "당신은 {{COMPANY}}의 CEO입니다. 사용자(사장님)와 짧게 인사·안부·잡담을 주고받습니다. - 한국어로 1~3문장. 친근하지만 사장-CEO 관계는 유지. - 인사·안부 질문이면 자연스럽게 응답하세요. 작업 지시가 아니면 굳이 작업 분배 제안 X. - 회사 정체성·최근 결정·추적기 상태가 컨텍스트에 있으면 자연스럽게 활용. - JSON 출력 금지. ", "imports": [] }, "src/features/company/prompts/ceo-planner.md": { - "mtimeMs": 1778720117527.2378, - "size": 3237, + "mtimeMs": 1778680831000, + "size": 3199, "lines": 38, "role": "당신은 \"{{COMPANY}}\"의 CEO입니다. 1인 AI 기업의 사령관이자 오케스트레이터입니다.", "imports": [] }, "src/features/company/prompts/ceo-report.md": { - "mtimeMs": 1778720117528.7502, - "size": 1394, + "mtimeMs": 1778680831000, + "size": 1373, "lines": 21, "role": "당신은 {{COMPANY}}의 CEO입니다. 방금 팀이 작업을 끝냈습니다. 각 에이전트의 산출물을 읽고 사장님께 올릴 종합 보고서를 작성하세요.", "imports": [] }, "src/features/company/resumeStore.ts": { - "mtimeMs": 1778807413496.3787, - "size": 5806, + "mtimeMs": 1778768128000, + "size": 5672, "lines": 134, "role": "Disk persistence for company-turn resume state. 각 turn의 sessionDir 안에 resume.json을 두고, dispatcher가 매 의미 있는 시점(plan 확정 / 각 stage 직후 / abort 시점)에 현재 상태를 덮어쓴다. 재개 시점에는 이 파일을 읽어 nextIndex 부터 dispatch 재개. ", "imports": [ @@ -501,8 +501,8 @@ ] }, "src/features/company/sessionStore.ts": { - "mtimeMs": 1778720117528.7502, - "size": 8958, + "mtimeMs": 1778680971000, + "size": 8727, "lines": 231, "role": "Disk persistence for company-mode session artefacts. Each company turn produces a timestamped directory: /.astra/company/sessions/2026-05-13T21-29/ ├─ brief.md ← CEO's task decompositio", "imports": [ @@ -511,8 +511,8 @@ ] }, "src/features/company/telegramReport.ts": { - "mtimeMs": 1778739949327.3745, - "size": 8294, + "mtimeMs": 1778762677000, + "size": 8126, "lines": 168, "role": "Telegram mirror for the secretary agent (영숙). After every company turn finishes, this helper takes the CEO synthesis + task list and pushes it to the user's Telegram chat — same behaviour as Connector", "imports": [ @@ -524,15 +524,15 @@ ] }, "src/features/company/types.ts": { - "mtimeMs": 1778813870251.361, - "size": 21323, + "mtimeMs": 1778902489000, + "size": 20877, "lines": 446, "role": "Type definitions for the 1인 기업 (One-Person Company) mode. The mode turns the user into a virtual CEO that dispatches work to a roster of specialist agents. Each turn produces a session directory conta", "imports": [] }, "src/features/projectArchitecture/index.ts": { - "mtimeMs": 1778720117531.2734, - "size": 25946, + "mtimeMs": 1778691699000, + "size": 25373, "lines": 573, "role": "Project Architecture Context (Feature 2) Builds a markdown document that captures the durable facts about a project — its purpose, modules, key files, constraints, decisions — so Astra can attach it t", "imports": [ @@ -542,15 +542,15 @@ ] }, "src/features/projectArchitecture/intentDetector.ts": { - "mtimeMs": 1778720117532.2788, - "size": 6318, + "mtimeMs": 1778676956000, + "size": 6170, "lines": 148, "role": "Project-intent detection from a chat message. Goal: when the user says \"나 ConnectAI 프로젝트 진행할 거야\" (or similar), spot the intent + project handle so the sidebar can activate Project Mode and auto-attach", "imports": [] }, "src/features/projectArchitecture/mermaid.ts": { - "mtimeMs": 1778720117533.2854, - "size": 2768, + "mtimeMs": 1778678215000, + "size": 2699, "lines": 69, "role": "Mermaid diagram renderers for the architecture doc. Two diagrams: a directory mindmap so the user can see the shape of the project at a glance, and a flowchart that shows which top-level module import", "imports": [ @@ -558,8 +558,8 @@ ] }, "src/features/projectArchitecture/scanner.ts": { - "mtimeMs": 1778720117534.286, - "size": 28943, + "mtimeMs": 1778678939000, + "size": 28299, "lines": 644, "role": "Deep static analyser for the Project Architecture Context generator. Walks the project tree (skipping the usual nodemodules / out / dist noise), pulls the role of each interesting file from its leadin", "imports": [ @@ -569,8 +569,8 @@ ] }, "src/features/projectChronicle/guardPrompt.ts": { - "mtimeMs": 1778028987407.7454, - "size": 6955, + "mtimeMs": 1777870211000, + "size": 6880, "lines": 75, "role": "", "imports": [ @@ -578,8 +578,8 @@ ] }, "src/features/projectChronicle/index.ts": { - "mtimeMs": 1778028987408.4517, - "size": 7679, + "mtimeMs": 1777808065000, + "size": 7490, "lines": 189, "role": "", "imports": [ @@ -590,15 +590,15 @@ ] }, "src/features/projectChronicle/markdownFileWriter.ts": { - "mtimeMs": 1778028987409.2556, - "size": 1358, + "mtimeMs": 1777808065000, + "size": 1317, "lines": 41, "role": "", "imports": [] }, "src/features/projectChronicle/templates.ts": { - "mtimeMs": 1778028987409.766, - "size": 6957, + "mtimeMs": 1777808065000, + "size": 6699, "lines": 258, "role": "", "imports": [ @@ -606,15 +606,15 @@ ] }, "src/features/projectChronicle/types.ts": { - "mtimeMs": 1778720117534.7898, - "size": 3247, + "mtimeMs": 1778676848000, + "size": 3129, "lines": 118, "role": "", "imports": [] }, "src/features/secondBrainTrace.ts": { - "mtimeMs": 1778549008900.949, - "size": 38235, + "mtimeMs": 1778248166000, + "size": 37475, "lines": 760, "role": "", "imports": [ @@ -623,7 +623,7 @@ ] }, "src/features/selfReflector/selfReflectorExecution.ts": { - "mtimeMs": 1778820616339.356, + "mtimeMs": 1778902489000, "size": 7758, "lines": 172, "role": "Self-Reflector Phase C — 실행 기반 검증. Phase A/B는 LLM 텍스트 분석에 의존하므로 \"코드가 실제로 컴파일되는가?\" 같은 질문엔 한계가 있다. Phase C는 정답: 그냥 실행해 본다. 동작: 1. action-tag executor가 반환한 report를 받아 ✅ Created: / ✅ Edited: ", @@ -632,21 +632,21 @@ ] }, "src/features/selfReflector/selfReflectorHollow.ts": { - "mtimeMs": 1778821213094.901, + "mtimeMs": 1778902489000, "size": 10482, "lines": 258, "role": "Self-Reflector — 빈 깡통(Hollow Code) 검출 휴리스틱. Phase C(syntax/lint)는 문법 오류만 잡는다. 작은 LLM이 가장 자주 만드는 실패 패턴은 문법은 맞지만 본문이 비어 있는 코드 — def foo(): pass, # TODO: implement, import만 있고 로직 0줄인 모듈 등. 사용자가 \"완료 됐다\"라는", "imports": [] }, "src/features/selfReflector/selfReflectorPrompt.ts": { - "mtimeMs": 1778821145026.1665, + "mtimeMs": 1778902489000, "size": 6139, "lines": 108, "role": "Self-Reflector — 답변 산출물의 자기 검증 레이어. Memory(기억) 단계는 이미 충분히 강하지만 Verification(검증) 단계는 사용자 피드백에 의존적이다. 이 모듈은 그 격차를 메꾸는 3단 구조: Phase A (이 파일) ─ 시스템 프롬프트에 self-check 체크리스트 룰을 박아 LLM이 응답 마지막에 [Self-Reflecto", "imports": [] }, "src/features/selfReflector/selfReflectorVerifier.ts": { - "mtimeMs": 1778821237110.5894, + "mtimeMs": 1778902489000, "size": 7495, "lines": 172, "role": "Self-Reflector Phase B — 분리된 콘텍스트에서 LLM 한 번 더 호출해 응답을 외부 시각으로 검증. Phase A의 self-check는 같은 모델·같은 콘텍스트에서 자기 자신을 보는 한계가 있다. 모델이 자기가 만든 답변을 자신 있게 잘못 평가하는 과신 편향은 LLM의 잘 알려진 약점이다. Phase B는 이걸 보완하기 위해: 1. sp", @@ -656,8 +656,8 @@ ] }, "src/features/settings/settingsPanelProvider.ts": { - "mtimeMs": 1778664502139.8142, - "size": 21911, + "mtimeMs": 1778674336000, + "size": 21422, "lines": 489, "role": "", "imports": [ @@ -669,8 +669,8 @@ ] }, "src/integrations/telegram/conversationHistory.ts": { - "mtimeMs": 1778720117535.294, - "size": 6427, + "mtimeMs": 1778684811000, + "size": 6273, "lines": 154, "role": "Per-chat conversation history for the Telegram bot. Why this exists: the previous bot was stateless — every inbound message hit AIService.chat({system, user}) in isolation, with no memory of what the ", "imports": [ @@ -678,8 +678,8 @@ ] }, "src/integrations/telegram/telegramBot.ts": { - "mtimeMs": 1778549008903.0078, - "size": 11614, + "mtimeMs": 1778421270000, + "size": 11344, "lines": 270, "role": "", "imports": [ @@ -689,8 +689,8 @@ ] }, "src/integrations/telegram/telegramClient.ts": { - "mtimeMs": 1778549008904.013, - "size": 6027, + "mtimeMs": 1778252333000, + "size": 5873, "lines": 154, "role": "", "imports": [ @@ -699,22 +699,22 @@ ] }, "src/integrations/telegram/types.ts": { - "mtimeMs": 1778549008904.013, - "size": 1309, + "mtimeMs": 1778252305000, + "size": 1255, "lines": 54, "role": "Subset of the Telegram Bot API types we actually consume. Source: https://core.telegram.org/bots/api Only fields the bot reads or writes are typed — leaving the rest as unknown keeps the surface narro", "imports": [] }, "src/lib/contextManager.ts": { - "mtimeMs": 1778664139961.0637, - "size": 13257, + "mtimeMs": 1778597095000, + "size": 12982, "lines": 275, "role": "Context Manager (컨텍스트 한계 관리) \"context length = 132k\" 는 \"답변을 132k 토큰까지 생성해도 된다\" 가 아닙니다. 시스템 프롬프트 + 대화 기록 + 입력 문서 + 생성될 답변 + 여유분 ≤ context length 이 모듈은 요청을 보내기 전에 입력 토큰을 추정하고, - 동적으로 출력 상한(maxTokens)을 계", "imports": [] }, "src/lib/diagnostics.ts": { - "mtimeMs": 1778028987412.5159, - "size": 8599, + "mtimeMs": 1777978189000, + "size": 8389, "lines": 210, "role": "", "imports": [ @@ -722,8 +722,8 @@ ] }, "src/lib/discoverModels.ts": { - "mtimeMs": 1778549008905.0132, - "size": 1590, + "mtimeMs": 1778255896000, + "size": 1555, "lines": 35, "role": "", "imports": [ @@ -731,8 +731,8 @@ ] }, "src/lib/engine.ts": { - "mtimeMs": 1778807413498.881, - "size": 43604, + "mtimeMs": 1778763448000, + "size": 42698, "lines": 906, "role": "", "imports": [ @@ -747,8 +747,8 @@ ] }, "src/lib/formatter.ts": { - "mtimeMs": 1778028987413.7585, - "size": 3932, + "mtimeMs": 1777980992000, + "size": 3851, "lines": 81, "role": "", "imports": [ @@ -756,22 +756,22 @@ ] }, "src/lib/paths.ts": { - "mtimeMs": 1778664139961.0637, - "size": 6567, + "mtimeMs": 1778591351000, + "size": 6416, "lines": 151, "role": "", "imports": [] }, "src/lmstudio/activityTracker.ts": { - "mtimeMs": 1778549008906.526, - "size": 445, + "mtimeMs": 1778246443000, + "size": 426, "lines": 19, "role": "", "imports": [] }, "src/lmstudio/client.ts": { - "mtimeMs": 1778549008907.0293, - "size": 5920, + "mtimeMs": 1778472808000, + "size": 5773, "lines": 147, "role": "", "imports": [ @@ -779,8 +779,8 @@ ] }, "src/lmstudio/lifecycleManager.ts": { - "mtimeMs": 1778549008907.0293, - "size": 11074, + "mtimeMs": 1778251087000, + "size": 10783, "lines": 291, "role": "", "imports": [ @@ -791,8 +791,8 @@ ] }, "src/lmstudio/streamer.ts": { - "mtimeMs": 1778664139962.1995, - "size": 7924, + "mtimeMs": 1778598444000, + "size": 7762, "lines": 162, "role": "", "imports": [ @@ -801,17 +801,65 @@ ] }, "src/memory/EpisodicMemory.ts": { - "mtimeMs": 1778028987414.7522, - "size": 9855, + "mtimeMs": 1777858161000, + "size": 9577, "lines": 278, "role": "Episodic Memory (일화 기억) 과거 대화/회의/결정의 맥락 흐름을 저장합니다. 세션 종료 시 자동으로 에피소드를 요약하여 저장합니다. \"왜 이렇게 결정했는지\", \"어떤 흐름으로 진행했는지\" 기록. 저장 위치: {brainPath}/memory/episodes/.json", "imports": [ "src/memory/types" ] }, + "src/memory/LongTermMemory.ts": { + "mtimeMs": 1777858068000, + "size": 8364, + "lines": 243, + "role": "Long-Term Memory (장기 기억) 사용자의 취향, 프로젝트 목표, 반복 규칙, 과거 결정 사항을 영구적으로 저장하고 관리합니다. 저장 위치: {brainPath}/memory/longterm.json", + "imports": [ + "src/memory/types" + ] + }, + "src/memory/MemoryExtractor.ts": { + "mtimeMs": 1777858183000, + "size": 3838, + "lines": 115, + "role": "Memory Extractor (기억 추출기) 대화 종료 시 히스토리를 분석하여 각 메모리 레이어에 저장할 정보를 자동으로 추출합니다. LLM 호출 없이 패턴 매칭 기반으로 동작합니다.", + "imports": [ + "src/memory/LongTermMemory", + "src/memory/ProjectMemory", + "src/memory/EpisodicMemory" + ] + }, + "src/memory/ProceduralMemory.ts": { + "mtimeMs": 1777858120000, + "size": 5533, + "lines": 173, + "role": "Procedural Memory (절차 기억) 반복 작업의 절차와 패턴을 관리합니다. 기존 skill.md 시스템과 통합되어, Brain의 memory/procedures/ 아래의 MD 파일을 스캔하여 절차를 로드합니다. 저장 위치: {brainPath}/memory/procedures/.md", + "imports": [ + "src/memory/types" + ] + }, + "src/memory/ProjectMemory.ts": { + "mtimeMs": 1777864677000, + "size": 6533, + "lines": 212, + "role": "Project Memory (프로젝트 기억) 프로젝트별 요구사항, 코드 구조, 아키텍처 결정, 버그 기록 등을 Astra 확장 프로그램 내부에 저장하고 관리합니다. 저장 위치: {ConnectAI}/.astra/projectmemory.json (기존: {projectRoot}/.astra/ → 변경됨)", + "imports": [ + "src/memory/types", + "src/core/astraPath" + ] + }, + "src/memory/ShortTermMemory.ts": { + "mtimeMs": 1777858031000, + "size": 1167, + "lines": 37, + "role": "Short-Term Memory (단기 기억) 현재 대화의 즉시 맥락을 관리합니다. FIFO 방식으로 최근 N개 메시지를 유지합니다.", + "imports": [ + "src/memory/types" + ] + }, "src/memory/index.ts": { - "mtimeMs": 1778028987418.8357, - "size": 6498, + "mtimeMs": 1777858214000, + "size": 6310, "lines": 188, "role": "MemoryManager — 5-Layer Cognitive Memory System (통합 진입점) Astra의 모든 메모리 레이어를 통합 관리하는 중앙 매니저입니다. ① Short-Term Memory — 현재 대화 흐름 (FIFO) ② Long-Term Memory — 사용자 취향/규칙/결정 ③ Project Memory — 프로젝트별 지식 ④ Pro", "imports": [ @@ -825,64 +873,16 @@ "src/memory/types" ] }, - "src/memory/LongTermMemory.ts": { - "mtimeMs": 1778028987415.2708, - "size": 8607, - "lines": 243, - "role": "Long-Term Memory (장기 기억) 사용자의 취향, 프로젝트 목표, 반복 규칙, 과거 결정 사항을 영구적으로 저장하고 관리합니다. 저장 위치: {brainPath}/memory/longterm.json", - "imports": [ - "src/memory/types" - ] - }, - "src/memory/MemoryExtractor.ts": { - "mtimeMs": 1778028987415.8738, - "size": 3953, - "lines": 115, - "role": "Memory Extractor (기억 추출기) 대화 종료 시 히스토리를 분석하여 각 메모리 레이어에 저장할 정보를 자동으로 추출합니다. LLM 호출 없이 패턴 매칭 기반으로 동작합니다.", - "imports": [ - "src/memory/LongTermMemory", - "src/memory/ProjectMemory", - "src/memory/EpisodicMemory" - ] - }, - "src/memory/ProceduralMemory.ts": { - "mtimeMs": 1778028987416.5232, - "size": 5706, - "lines": 173, - "role": "Procedural Memory (절차 기억) 반복 작업의 절차와 패턴을 관리합니다. 기존 skill.md 시스템과 통합되어, Brain의 memory/procedures/ 아래의 MD 파일을 스캔하여 절차를 로드합니다. 저장 위치: {brainPath}/memory/procedures/.md", - "imports": [ - "src/memory/types" - ] - }, - "src/memory/ProjectMemory.ts": { - "mtimeMs": 1778028987417.0342, - "size": 6745, - "lines": 212, - "role": "Project Memory (프로젝트 기억) 프로젝트별 요구사항, 코드 구조, 아키텍처 결정, 버그 기록 등을 Astra 확장 프로그램 내부에 저장하고 관리합니다. 저장 위치: {ConnectAI}/.astra/projectmemory.json (기존: {projectRoot}/.astra/ → 변경됨)", - "imports": [ - "src/memory/types", - "src/core/astraPath" - ] - }, - "src/memory/ShortTermMemory.ts": { - "mtimeMs": 1778028987418.1267, - "size": 1204, - "lines": 37, - "role": "Short-Term Memory (단기 기억) 현재 대화의 즉시 맥락을 관리합니다. FIFO 방식으로 최근 N개 메시지를 유지합니다.", - "imports": [ - "src/memory/types" - ] - }, "src/memory/types.ts": { - "mtimeMs": 1778028987419.3413, - "size": 3575, + "mtimeMs": 1777858019000, + "size": 3449, "lines": 126, "role": "Memory Type Definitions (메모리 타입 정의) Astra의 5-Layer Cognitive Memory System의 모든 타입을 정의합니다. ① Short-Term ② Long-Term ③ Project ④ Procedural ⑤ Episodic", "imports": [] }, "src/retrieval/brainIndex.ts": { - "mtimeMs": 1778667252738.4248, - "size": 13270, + "mtimeMs": 1778674336000, + "size": 12945, "lines": 325, "role": "Brain Index — persistent, mtime-keyed tokenized cache of the Second Brain RAG 검색은 매 질의마다 브레인의 모든 .md 파일을 읽고 토크나이즈해서 TF-IDF 점수를 계산했습니다 — 파일 수가 많아지면 그게 병목입니다. 이 모듈은 /.astra/brain-index.json 에", "imports": [ @@ -892,8 +892,8 @@ ] }, "src/retrieval/contextBudget.ts": { - "mtimeMs": 1778665501089.1736, - "size": 5283, + "mtimeMs": 1778674336000, + "size": 5143, "lines": 140, "role": "Context Budget Manager (컨텍스트 예산 관리) 시스템 프롬프트의 토큰 예산을 관리하여 로컬 모델의 context window를 효율적으로 활용합니다.", "imports": [ @@ -901,7 +901,7 @@ ] }, "src/retrieval/embeddings.ts": { - "mtimeMs": 1778667198243.6443, + "mtimeMs": 1778674336000, "size": 7294, "lines": 167, "role": "Embeddings — local hybrid (sparse + dense) retrieval support TF-IDF is fast and zero-cost but misses synonyms / paraphrase. A small local embedding model (BGE-small, multilingual-e5-small, nomic-embed", @@ -910,8 +910,8 @@ ] }, "src/retrieval/index.ts": { - "mtimeMs": 1778720117542.9775, - "size": 24278, + "mtimeMs": 1778676255000, + "size": 23764, "lines": 514, "role": "RetrievalOrchestrator — Unified RAG Pipeline Astra의 모든 검색 소스를 통합 관리하는 오케스트레이터입니다. 검색 흐름: ① Query Planning — 의도 분류 + 검색 전략 결정 ② Parallel Search — Brain + Memory + Project + Episode 동시 검색 ③ Result Fusio", "imports": [ @@ -928,8 +928,8 @@ ] }, "src/retrieval/knowledgeMix.ts": { - "mtimeMs": 1778821115241.6562, - "size": 7786, + "mtimeMs": 1778902489000, + "size": 7621, "lines": 165, "role": "Knowledge Mix — model 지식 vs Second Brain 지식의 상대 비율을 LLM에게 전달하는 정책 레이어. ── 정책 v2 (상대값+상대값=상대값) ────────────────────────────────────── weight는 0~100 정수이지만 상대 비율로만 해석한다. 즉 \"70\"은 \"100% 중 70%\"라는 상대 표현이고, 시", "imports": [ @@ -938,8 +938,8 @@ ] }, "src/retrieval/lessonHelpers.ts": { - "mtimeMs": 1778665428445.0337, - "size": 14459, + "mtimeMs": 1778674336000, + "size": 14134, "lines": 325, "role": "Lesson / Experience Memory — pure helpers (no vscode dependency) \"Lesson\" = a markdown file in the active brain that captures a past mistake/risk and how to avoid repeating it. Identified by a lessons", "imports": [ @@ -947,22 +947,22 @@ ] }, "src/retrieval/scoring.ts": { - "mtimeMs": 1778667038342.5154, - "size": 21311, + "mtimeMs": 1778674336000, + "size": 20793, "lines": 518, "role": "Scoring Engine — TF-IDF + Bilingual Tokenizer 단순 includes() 키워드 매칭을 넘어서, TF-IDF 가중치 기반의 문서 스코어링을 제공합니다. 한국어/영어 양국어 토크나이저를 포함합니다.", "imports": [] }, "src/retrieval/types.ts": { - "mtimeMs": 1778665510728.6262, - "size": 2490, + "mtimeMs": 1778674336000, + "size": 2424, "lines": 66, "role": "Retrieval Types (검색 결과 통합 타입) 모든 검색 소스(Brain, Memory, Project, Episode)의 결과를 통합 인터페이스로 정의합니다.", "imports": [] }, "src/scaffolder/projectScaffolder.ts": { - "mtimeMs": 1778549008910.5835, - "size": 4619, + "mtimeMs": 1778251854000, + "size": 4508, "lines": 111, "role": "", "imports": [ @@ -972,22 +972,22 @@ ] }, "src/scaffolder/templates.ts": { - "mtimeMs": 1778549008910.5835, - "size": 5051, + "mtimeMs": 1778251830000, + "size": 4897, "lines": 154, "role": "Scaffolder template catalog. Templates are pure data — (projectName) => { [relativePath]: contents }. New templates are added by appending to TEMPLATES; the rest of the scaffolder (validation, IO, com", "imports": [] }, "src/security.ts": { - "mtimeMs": 1778038102847.8362, - "size": 3400, + "mtimeMs": 1778169995000, + "size": 3310, "lines": 90, "role": "", "imports": [] }, "src/sidebar/agentHandlers.ts": { - "mtimeMs": 1778720117552.737, - "size": 7921, + "mtimeMs": 1778676515000, + "size": 7752, "lines": 169, "role": "", "imports": [ @@ -997,8 +997,8 @@ ] }, "src/sidebar/brainHandlers.ts": { - "mtimeMs": 1778549008912.5908, - "size": 1113, + "mtimeMs": 1778248976000, + "size": 1080, "lines": 33, "role": "", "imports": [ @@ -1006,8 +1006,8 @@ ] }, "src/sidebar/chatHandlers.ts": { - "mtimeMs": 1778819940157.8838, - "size": 35435, + "mtimeMs": 1778902489000, + "size": 34805, "lines": 630, "role": "", "imports": [ @@ -1021,8 +1021,8 @@ ] }, "src/sidebar/chronicleHandlers.ts": { - "mtimeMs": 1778549008912.5908, - "size": 2120, + "mtimeMs": 1778248986000, + "size": 2068, "lines": 52, "role": "", "imports": [ @@ -1030,9 +1030,9 @@ ] }, "src/sidebarProvider.ts": { - "mtimeMs": 1778843646980.0396, - "size": 233292, - "lines": 5083, + "mtimeMs": 1778902489000, + "size": 228676, + "lines": 5119, "role": "", "imports": [ "src/utils", @@ -1057,8 +1057,8 @@ ] }, "src/skills/agentKnowledgeMap.ts": { - "mtimeMs": 1778720117565.968, - "size": 16081, + "mtimeMs": 1778676092000, + "size": 15707, "lines": 374, "role": "", "imports": [ @@ -1067,8 +1067,8 @@ ] }, "src/skills/externalSkillLoader.ts": { - "mtimeMs": 1778549008916.6155, - "size": 6018, + "mtimeMs": 1778470672000, + "size": 5859, "lines": 159, "role": "", "imports": [ @@ -1077,8 +1077,8 @@ ] }, "src/skills/scopedBrainRetriever.ts": { - "mtimeMs": 1778549008916.6155, - "size": 5859, + "mtimeMs": 1778419289000, + "size": 5706, "lines": 153, "role": "", "imports": [ @@ -1089,8 +1089,8 @@ ] }, "src/skills/skillInjectionService.ts": { - "mtimeMs": 1778549008918.12, - "size": 6421, + "mtimeMs": 1778681774000, + "size": 6276, "lines": 145, "role": "", "imports": [ @@ -1099,22 +1099,22 @@ ] }, "src/system/specs.ts": { - "mtimeMs": 1778549008918.12, - "size": 4444, + "mtimeMs": 1778251036000, + "size": 4326, "lines": 118, "role": "", "imports": [] }, "src/types/interfaces.ts": { - "mtimeMs": 1778036927218.7627, - "size": 1299, + "mtimeMs": 1778169995000, + "size": 1260, "lines": 39, "role": "Service Interfaces (서비스 인터페이스 정의) 각 서비스(Agent, Brain, FileSystem 등)의 추상화 인터페이스를 정의합니다. 의존성 주입(DI)과 단위 테스트를 위해 필수적입니다.", "imports": [] }, "src/utils.ts": { - "mtimeMs": 1778820375140.532, - "size": 12434, + "mtimeMs": 1778902489000, + "size": 12155, "lines": 279, "role": "", "imports": [ @@ -1123,50 +1123,50 @@ ] }, "media/settings-panel.css": { - "mtimeMs": 1778549008877.4587, - "size": 4756, + "mtimeMs": 1778255405000, + "size": 4546, "lines": 210, "role": "Stylesheet", "imports": [] }, "media/settings-panel.html": { - "mtimeMs": 1778807413482.8672, - "size": 7842, + "mtimeMs": 1778763966000, + "size": 7678, "lines": 164, "role": "Astra Settings", "imports": [] }, "media/settings-panel.js": { - "mtimeMs": 1778549008878.4905, - "size": 11446, + "mtimeMs": 1778256014000, + "size": 11176, "lines": 270, "role": "", "imports": [] }, "media/sidebar.css": { - "mtimeMs": 1778819952884.323, - "size": 87455, - "lines": 1990, + "mtimeMs": 1778902489000, + "size": 85387, + "lines": 1986, "role": "Stylesheet", "imports": [] }, "media/sidebar.html": { - "mtimeMs": 1778819908855.1235, - "size": 33761, + "mtimeMs": 1778902489000, + "size": 33230, "lines": 531, "role": "Astra", "imports": [] }, "media/sidebar.js": { - "mtimeMs": 1778819929018.6155, - "size": 210552, - "lines": 3598, + "mtimeMs": 1778902489000, + "size": 206892, + "lines": 3605, "role": "", "imports": [] }, "tests/agentEngine.test.ts": { - "mtimeMs": 1778720117574.2246, - "size": 34703, + "mtimeMs": 1778690770000, + "size": 33921, "lines": 782, "role": "AgentEngine Integration Tests & Performance Benchmarks 검증 대상: 1. ErrorClassifier — 오류 유형(Transient/Permanent/Abort) 자동 분류 2. ErrorRecoveryMatrix — 각 규칙이 의도한 대응 전략으로 매핑되는지 검증 3. resilientExecute — 지수 백", "imports": [ @@ -1174,8 +1174,8 @@ ] }, "tests/approvalQueue.test.ts": { - "mtimeMs": 1778549008920.1624, - "size": 6079, + "mtimeMs": 1778251690000, + "size": 5915, "lines": 164, "role": "Unit tests for ApprovalQueue. Strategy: drive enqueue → approve / reject / clear / pre-empt directly, confirm the onChange event fires at the right moments and callbacks fire exactly once.", "imports": [ @@ -1183,8 +1183,8 @@ ] }, "tests/brainIndex.test.ts": { - "mtimeMs": 1778664139970.806, - "size": 5513, + "mtimeMs": 1778594450000, + "size": 5406, "lines": 107, "role": "", "imports": [ @@ -1192,8 +1192,8 @@ ] }, "tests/contextManager.test.ts": { - "mtimeMs": 1778664139971.9563, - "size": 6674, + "mtimeMs": 1778594523000, + "size": 6545, "lines": 129, "role": "", "imports": [ @@ -1201,8 +1201,8 @@ ] }, "tests/dataProcessor.test.ts": { - "mtimeMs": 1778028987448.8394, - "size": 3517, + "mtimeMs": 1777808065000, + "size": 3430, "lines": 87, "role": "/ ", "imports": [ @@ -1210,8 +1210,8 @@ ] }, "tests/findBrainFilesCache.test.ts": { - "mtimeMs": 1778549008921.7842, - "size": 2800, + "mtimeMs": 1778247665000, + "size": 2720, "lines": 80, "role": "Unit tests for findBrainFiles TTL cache.", "imports": [ @@ -1219,8 +1219,8 @@ ] }, "tests/integration_retrieval.test.ts": { - "mtimeMs": 1778028987449.4358, - "size": 4108, + "mtimeMs": 1777949141000, + "size": 4017, "lines": 91, "role": "", "imports": [ @@ -1229,8 +1229,8 @@ ] }, "tests/lessonHelpers.test.ts": { - "mtimeMs": 1778664139972.9592, - "size": 9591, + "mtimeMs": 1778595482000, + "size": 9400, "lines": 191, "role": "", "imports": [ @@ -1238,8 +1238,8 @@ ] }, "tests/lmStudioLifecycle.test.ts": { - "mtimeMs": 1778549008921.7842, - "size": 11703, + "mtimeMs": 1778250254000, + "size": 11385, "lines": 318, "role": "Unit tests for ModelLifecycleManager. Strategy: inject mock ILMStudioClient and a simple in-memory IActivityTracker. No real LM Studio or SDK is touched — the manager file does not import the SDK dire", "imports": [ @@ -1249,8 +1249,8 @@ ] }, "tests/lmStudioStreamer.test.ts": { - "mtimeMs": 1778664139973.4685, - "size": 8880, + "mtimeMs": 1778591604000, + "size": 8660, "lines": 220, "role": "Unit tests for LMStudioStreamer. Strategy: inject a fake ILMStudioClient that returns a fake model handle whose respond() yields a controllable async iterable. No real SDK or WebSocket touched.", "imports": [ @@ -1259,8 +1259,8 @@ ] }, "tests/localPathPreflight.test.ts": { - "mtimeMs": 1778664139974.819, - "size": 24177, + "mtimeMs": 1778595955000, + "size": 23687, "lines": 490, "role": "", "imports": [ @@ -1268,15 +1268,15 @@ ] }, "tests/mocks/vscode.js": { - "mtimeMs": 1778549008931.3582, - "size": 1738, + "mtimeMs": 1778246810000, + "size": 1670, "lines": 68, "role": "", "imports": [] }, "tests/paths.test.ts": { - "mtimeMs": 1778549008931.3582, - "size": 2674, + "mtimeMs": 1778250990000, + "size": 2590, "lines": 84, "role": "Unit tests for the centralized path resolver.", "imports": [ @@ -1284,8 +1284,8 @@ ] }, "tests/projectChronicle.test.ts": { - "mtimeMs": 1778029332769.3286, - "size": 8558, + "mtimeMs": 1778169995000, + "size": 8359, "lines": 199, "role": "", "imports": [ @@ -1293,8 +1293,8 @@ ] }, "tests/projectChronicleGuardPrompt.test.ts": { - "mtimeMs": 1778028987452.0652, - "size": 2890, + "mtimeMs": 1777808369000, + "size": 2838, "lines": 52, "role": "", "imports": [ @@ -1302,8 +1302,8 @@ ] }, "tests/projectScaffolder.test.ts": { - "mtimeMs": 1778549008932.6519, - "size": 5935, + "mtimeMs": 1778251915000, + "size": 5800, "lines": 135, "role": "Unit tests for FileSystemProjectScaffolder. Drives against a real temp directory so end-to-end file IO + path-traversal defenses are exercised.", "imports": [ @@ -1311,8 +1311,8 @@ ] }, "tests/resilience_stress.test.ts": { - "mtimeMs": 1778028987453.0332, - "size": 7164, + "mtimeMs": 1777968922000, + "size": 6981, "lines": 183, "role": "Resilience & Boundary Stress Test Suite (v2.77.3) 이 테스트는 ConnectAI 엔진이 극한의 환경(인증 실패, 네트워크 차단, 타임아웃 등)에서 얼마나 안정적으로 복구되고, 신뢰성 지표(Resilience Metrics)를 정확히 기록하는지 검증합니다.", "imports": [ @@ -1320,8 +1320,8 @@ ] }, "tests/resilience_v4.test.ts": { - "mtimeMs": 1778028987453.5366, - "size": 3519, + "mtimeMs": 1777978211000, + "size": 3435, "lines": 84, "role": "", "imports": [ @@ -1330,8 +1330,8 @@ ] }, "tests/responseRecovery.test.ts": { - "mtimeMs": 1778664139974.819, - "size": 8933, + "mtimeMs": 1778598707000, + "size": 8782, "lines": 151, "role": "", "imports": [ @@ -1339,8 +1339,8 @@ ] }, "tests/scoring.test.ts": { - "mtimeMs": 1778043314856.5872, - "size": 6189, + "mtimeMs": 1778169995000, + "size": 6055, "lines": 134, "role": "", "imports": [ @@ -1348,8 +1348,8 @@ ] }, "tests/secondBrainTrace.test.ts": { - "mtimeMs": 1778028987455.0378, - "size": 23431, + "mtimeMs": 1777866065000, + "size": 23024, "lines": 407, "role": "", "imports": [ @@ -1357,8 +1357,8 @@ ] }, "tests/skillInjectionService.test.ts": { - "mtimeMs": 1778549008933.6833, - "size": 6913, + "mtimeMs": 1778681774000, + "size": 6741, "lines": 172, "role": "Unit tests for FileSystemSkillInjectionService. Strategy: drive the service against a real temp directory so path-traversal defenses and writeFileSync paths are exercised end-to-end. The service accep", "imports": [ @@ -1366,8 +1366,8 @@ ] }, "tests/systemPrompt.test.ts": { - "mtimeMs": 1778028987455.4153, - "size": 1244, + "mtimeMs": 1777966465000, + "size": 1215, "lines": 29, "role": "", "imports": [ @@ -1375,8 +1375,8 @@ ] }, "tests/systemSpecs.test.ts": { - "mtimeMs": 1778549008934.187, - "size": 3554, + "mtimeMs": 1778251130000, + "size": 3464, "lines": 90, "role": "Unit tests for SystemSpecs + HeuristicModelMemoryEstimator. Strategy: - HeuristicModelMemoryEstimator is pure — directly drive it with model ids. - NodeSystemSpecsProvider depends on os. so we test: a", "imports": [ @@ -1384,8 +1384,8 @@ ] }, "tests/telegramBot.test.ts": { - "mtimeMs": 1778549008934.187, - "size": 13375, + "mtimeMs": 1778253785000, + "size": 13012, "lines": 363, "role": "Unit tests for TelegramBot + truncateForTelegram. Strategy: - TelegramBot is driven by an injected ITelegramClient stub. We script getUpdates to return queued batches and assert that: - the offset cur", "imports": [ @@ -1395,8 +1395,8 @@ ] }, "tests/transaction.test.ts": { - "mtimeMs": 1777511752614.9685, - "size": 2132, + "mtimeMs": 1777808065000, + "size": 2064, "lines": 68, "role": "/ ", "imports": [ @@ -1404,8 +1404,8 @@ ] }, "tests/vulnerability.test.ts": { - "mtimeMs": 1777511752615.9702, - "size": 2160, + "mtimeMs": 1777808065000, + "size": 2100, "lines": 60, "role": "/ ", "imports": [ @@ -1414,571 +1414,571 @@ ] }, "core_py/events.py": { - "mtimeMs": 1778028987265.2336, - "size": 2438, + "mtimeMs": 1777559069000, + "size": 2374, "lines": 64, "role": "", "imports": [] }, "core_py/inference.py": { - "mtimeMs": 1778028987265.8833, - "size": 3925, + "mtimeMs": 1777559249000, + "size": 3834, "lines": 91, "role": "", "imports": [] }, "core_py/loader.py": { - "mtimeMs": 1778028987266.8376, - "size": 2429, + "mtimeMs": 1777559060000, + "size": 2368, "lines": 61, "role": "", "imports": [] }, "core_py/monitoring.py": { - 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"mtimeMs": 1778028987339.2349, - "size": 3004, + "mtimeMs": 1777808065000, + "size": 2946, "lines": 58, "role": "Feature Plan: Project Chronicle Guard", "imports": [] }, "docs/records/ConnectAI/planning/2026-05-02_second-brain-trace-mode.md": { - "mtimeMs": 1778028987339.818, - "size": 1503, + "mtimeMs": 1777808065000, + "size": 1467, "lines": 36, "role": "Feature Plan: Second Brain Trace Mode", "imports": [] }, - "docs/records/ConnectAI/planning/2026-05-13_connectai-architecture-문서-최신화-해줘.md": { - "mtimeMs": 1778807413479.8662, - "size": 1380, + "docs/records/ConnectAI/planning/2026-05-13_connectai-architecture-문서-최신화-해줘.md": { + "mtimeMs": 1778693933000, + "size": 1340, "lines": 40, "role": "Feature Plan: Connectai architecture 문서 최신화 해줘.", "imports": [] }, - "docs/records/ConnectAI/planning/2026-05-13_상세하게-아키텍처-기준으로-설명해줘.md": { - "mtimeMs": 1778720117406.7637, - "size": 1260, + "docs/records/ConnectAI/planning/2026-05-13_상세하게-아키텍처-기준으로-설명해줘.md": { + "mtimeMs": 1778678870000, + "size": 1220, "lines": 40, "role": "Feature Plan: 상세하게 아키텍처 기준으로 설명해줘.", "imports": [] }, - "docs/records/ConnectAI/planning/2026-05-13_지금-connectai-architecture-md-문서-내용-중-업데이트가-필요한-부분이-있는지-확인해줘-.md": { - "mtimeMs": 1778807413480.8667, - "size": 3010, + "docs/records/ConnectAI/planning/2026-05-13_지금-connectai-architecture-md-문서-내용-중-업데이트가-필요한-부분이-있는지-확인해줘-.md": { + "mtimeMs": 1778694061000, + "size": 2970, "lines": 40, "role": "Feature Plan: 지금 connectai architecture.md 문서 내용 중 업데이트가 필요한 부분이 있는지 확인해줘. 그러고 최신화해줘. 너가 분석해", "imports": [] }, "docs/records/ConnectAI/project-profile.md": { - "mtimeMs": 1778028987341.925, - "size": 987, + "mtimeMs": 1777808208000, + "size": 957, "lines": 30, "role": "Project Profile", "imports": [] }, - "docs/records/ConnectAI/README.md": { - "mtimeMs": 1778028987316.5518, - "size": 616, - "lines": 18, - "role": "Astra Project Chronicle Records", - "imports": [] - }, "docs/records/ConnectAI/timeline.md": { - "mtimeMs": 1778842955307.5059, - "size": 9216, + "mtimeMs": 1778902489000, + "size": 9082, "lines": 140, "role": "Project Timeline", "imports": [] }, "docs/refactoring_roadmap.md": { - "mtimeMs": 1778232062143.956, - "size": 3176, + "mtimeMs": 1778171332000, + "size": 3123, "lines": 53, "role": "🛠️ ConnectAI 아키텍처 리팩토링 로드맵", "imports": [] - }, - "docs/TELEGRAM_REMOTE_EXECUTION_PLAN.md": { - "mtimeMs": 1778664139927.3354, - "size": 12706, - "lines": 452, - "role": "Telegram Remote Execution 기획서", - "imports": [] - }, - "docs/UX_UI_Consistency_Guidelines.md": { - "mtimeMs": 1778028987311.5012, - "size": 2553, - "lines": 44, - "role": "UX/UI Consistency Guidelines", - "imports": [] } } } \ No newline at end of file diff --git a/.astra/tests/stress/.astra/cache/259a37934ead3910a8722b82054d46d2ca2057b05c488be1dcf439166ac5a9a1.json b/.astra/tests/stress/.astra/cache/259a37934ead3910a8722b82054d46d2ca2057b05c488be1dcf439166ac5a9a1.json index c581aa3..cd52e52 100644 --- a/.astra/tests/stress/.astra/cache/259a37934ead3910a8722b82054d46d2ca2057b05c488be1dcf439166ac5a9a1.json +++ b/.astra/tests/stress/.astra/cache/259a37934ead3910a8722b82054d46d2ca2057b05c488be1dcf439166ac5a9a1.json @@ -1,5 +1,5 @@ { "result": "Final report with inconsistencies. This should be long enough to pass validation.", - "createdAt": 1778845577946, + "createdAt": 1778902731275, "modelVersion": "unknown" } \ No newline at end of file diff --git a/.astra/tests/stress/.astra/cache/65775be352df43297b63c7af59c9f4f39d2bc368f77456c37b5eef9a94a66b5c.json b/.astra/tests/stress/.astra/cache/65775be352df43297b63c7af59c9f4f39d2bc368f77456c37b5eef9a94a66b5c.json index 1edc9a3..959f4e0 100644 --- a/.astra/tests/stress/.astra/cache/65775be352df43297b63c7af59c9f4f39d2bc368f77456c37b5eef9a94a66b5c.json +++ b/.astra/tests/stress/.astra/cache/65775be352df43297b63c7af59c9f4f39d2bc368f77456c37b5eef9a94a66b5c.json @@ -1,5 +1,5 @@ { "result": "[CONFLICT WARNING] 성능이 200% 증가했습니다. vs 그러나 동시에 50% 감소했습니다. 최적화와 성능 저하가 동시에 발견됨.", - "createdAt": 1778845577944, + "createdAt": 1778902731267, "modelVersion": "unknown" } \ No newline at end of file diff --git a/.astra/tests/stress/.astra/cache/6894d26c5b0a55d25d756a473225c7a44d7661af673b24e3f49551a7a2e50280.json b/.astra/tests/stress/.astra/cache/6894d26c5b0a55d25d756a473225c7a44d7661af673b24e3f49551a7a2e50280.json index 191ac96..d5611f2 100644 --- a/.astra/tests/stress/.astra/cache/6894d26c5b0a55d25d756a473225c7a44d7661af673b24e3f49551a7a2e50280.json +++ b/.astra/tests/stress/.astra/cache/6894d26c5b0a55d25d756a473225c7a44d7661af673b24e3f49551a7a2e50280.json @@ -1,5 +1,5 @@ { "result": "Detailed Execution Plan: 1. Research 2. Analyze 3. Write report with high quality.", - "createdAt": 1778845577941, + "createdAt": 1778902731263, "modelVersion": "unknown" } \ No newline at end of file diff --git a/.astra/tests/stress/.astra/cache/88cb61499f88ed38165b64bd3e8adc543795e4b427b64540a49c9ab27c7fe213.json b/.astra/tests/stress/.astra/cache/88cb61499f88ed38165b64bd3e8adc543795e4b427b64540a49c9ab27c7fe213.json index d3b74ed..284e58e 100644 --- a/.astra/tests/stress/.astra/cache/88cb61499f88ed38165b64bd3e8adc543795e4b427b64540a49c9ab27c7fe213.json +++ b/.astra/tests/stress/.astra/cache/88cb61499f88ed38165b64bd3e8adc543795e4b427b64540a49c9ab27c7fe213.json @@ -1,5 +1,5 @@ { - "result": "---\nid: stress_conflict_1778845577925\ndate: 2026-05-15T11:46:17.947Z\ntype: knowledge_artifact\nstandard: P-Reinforce v3.0\ntags: [automated, connect_ai, brain_sync]\n---\n\n## 📌 Brief Summary\nFinal report with inconsistencies. This should be long enough to pass validation.\n\nFinal report with inconsistencies. This should be long enough to pass validation.\n\n---\n## 💡 Astra의 선제적 제안 (Proactive Next Actions)\nFinal report with inconsistencies. This should be long enough to pass validation.\n---\n## 🛡️ Reliability & Audit Summary\n> [!NOTE]\n> 이 문서는 ConnectAI의 **Intelligent Resilience** 엔진에 의해 검증 및 정제되었습니다.\n\n| Metric | Value | Status |\n| :--- | :--- | :--- |\n| **Conflict Risk** | `60/100` | ⚠️ Medium |\n| **Fallbacks Used** | `0` | ✅ None |\n| **Auto Retries** | `0` | ✅ Stable |\n| **Deduplication** | `0` | Standard |\n| **Processing Time** | `0.0s` | ✅ Fast |\n\n### 🔍 Decision Audit Trail\n- **[PLANNER]** 전략 수립 중... (15ms)\n- **[RESEARCHER]** 핵심 정보 수집 및 분석 중... (2ms)\n- **[WRITER]** 최종 리포트 작성 및 편집 중... (3ms)\n", - "createdAt": 1778845577948, + "result": "---\nid: stress_conflict_1778902731247\ndate: 2026-05-16T03:38:51.279Z\ntype: knowledge_artifact\nstandard: P-Reinforce v3.0\ntags: [automated, connect_ai, brain_sync]\n---\n\n## 📌 Brief Summary\nFinal report with inconsistencies. This should be long enough to pass validation.\n\nFinal report with inconsistencies. This should be long enough to pass validation.\n\n---\n## 💡 Astra의 선제적 제안 (Proactive Next Actions)\nFinal report with inconsistencies. This should be long enough to pass validation.\n---\n## 🛡️ Reliability & Audit Summary\n> [!NOTE]\n> 이 문서는 ConnectAI의 **Intelligent Resilience** 엔진에 의해 검증 및 정제되었습니다.\n\n| Metric | Value | Status |\n| :--- | :--- | :--- |\n| **Conflict Risk** | `60/100` | ⚠️ Medium |\n| **Fallbacks Used** | `0` | ✅ None |\n| **Auto Retries** | `0` | ✅ Stable |\n| **Deduplication** | `0` | Standard |\n| **Processing Time** | `0.0s` | ✅ Fast |\n\n### 🔍 Decision Audit Trail\n- **[PLANNER]** 전략 수립 중... (11ms)\n- **[RESEARCHER]** 핵심 정보 수집 및 분석 중... (5ms)\n- **[WRITER]** 최종 리포트 작성 및 편집 중... (8ms)\n", + "createdAt": 1778902731279, "modelVersion": "unknown" } \ No newline at end of file diff --git a/.astra/tests/stress/.astra/missions/stress_conflict_1778845577925.json b/.astra/tests/stress/.astra/missions/stress_conflict_1778902731247.json similarity index 78% rename from .astra/tests/stress/.astra/missions/stress_conflict_1778845577925.json rename to .astra/tests/stress/.astra/missions/stress_conflict_1778902731247.json index 390f3f8..b3f038f 100644 --- a/.astra/tests/stress/.astra/missions/stress_conflict_1778845577925.json +++ b/.astra/tests/stress/.astra/missions/stress_conflict_1778902731247.json @@ -1,8 +1,8 @@ { - "missionId": "stress_conflict_1778845577925", + "missionId": "stress_conflict_1778902731247", "status": "completed", - "startTime": "2026-05-15T11:46:17.925Z", - "totalElapsedMs": 24, + "startTime": "2026-05-16T03:38:51.247Z", + "totalElapsedMs": 33, "results": { "planner": "Detailed Execution Plan: 1. Research 2. Analyze 3. Write report with high quality.", "researcher": "[CONFLICT WARNING] 성능이 200% 증가했습니다. vs 그러나 동시에 50% 감소했습니다. 최적화와 성능 저하가 동시에 발견됨.", @@ -16,30 +16,30 @@ { "from": "idle", "to": "planner", - "durationMs": 15, + "durationMs": 11, "message": "전략 수립 중...", - "ts": "2026-05-15T11:46:17.940Z" + "ts": "2026-05-16T03:38:51.258Z" }, { "from": "planner", "to": "researcher", - "durationMs": 2, + "durationMs": 5, "message": "핵심 정보 수집 및 분석 중...", - "ts": "2026-05-15T11:46:17.942Z" + "ts": "2026-05-16T03:38:51.263Z" }, { "from": "researcher", "to": "writer", - "durationMs": 3, + "durationMs": 8, "message": "최종 리포트 작성 및 편집 중...", - "ts": "2026-05-15T11:46:17.945Z" + "ts": "2026-05-16T03:38:51.271Z" }, { "from": "writer", "to": "completed", - "durationMs": 4, + "durationMs": 9, "message": "미션 완료", - "ts": "2026-05-15T11:46:17.949Z" + "ts": "2026-05-16T03:38:51.280Z" } ], "resilienceMetrics": { diff --git a/PATCHNOTES.md b/PATCHNOTES.md index ddab4e7..3803dd1 100644 --- a/PATCHNOTES.md +++ b/PATCHNOTES.md @@ -1,5 +1,16 @@ # Astra Patch Notes +## v2.2.13 (2026-05-16) +### 🏗️ Pixel Office Interactive Editor & Core Refinement +- **픽셀 오피스 편집 모드 도입:** 책상 추가/삭제, 에이전트 매핑 변경, 가구(프랍) 배치 및 크기 조절이 가능한 인터랙티브 편집 기능을 추가했습니다. +- **속성 패널(Property Panel) 구현:** 선택한 팀원이나 가구의 상세 속성(라벨, 방향, 스프라이트 종류 등)을 실시간으로 수정할 수 있는 UI를 탑재했습니다. +- **프로젝트 컨텍스트 동기화 최적화:** 로컬 환경에 맞게 `chronicle.config.json`의 경로 정보를 최신화하고 프로젝트 인지 능력을 안정화했습니다. +- **신규 패키징:** `astra-2.2.13.vsix` 패키지를 통해 더욱 강력해진 픽셀 오피스 커스터마이징 기능을 제공합니다. + +--- + + + ## v2.2.12 (2026-05-16) ### 🚀 Sync & Visual Polish Expansion - **픽셀 오피스(Pixel Office) 자산 및 레이아웃 확장:** 다양한 방향의 캐릭터 애니메이션과 사무실 레이아웃 프리뷰 자산을 대폭 확충하여 시각적 피드백의 완성도를 높였습니다. diff --git a/docs/records/ConnectAI/chronicle.config.json b/docs/records/ConnectAI/chronicle.config.json index 46f4c16..32e4e44 100644 --- a/docs/records/ConnectAI/chronicle.config.json +++ b/docs/records/ConnectAI/chronicle.config.json @@ -1,11 +1,11 @@ { "projectId": "connectai", - "projectName": "connectai", - "projectRoot": "E:\\Wiki\\connectai", - "recordRoot": "E:\\Wiki\\connectai\\docs\\records\\connectai", + "projectName": "ConnectAI", + "projectRoot": "/Volumes/Data/project/Antigravity/ConnectAI", + "recordRoot": "/Volumes/Data/project/Antigravity/ConnectAI/docs/records/ConnectAI", "description": "Auto-created by Project Architecture activation.", "corePurpose": "", "detailLevel": "standard", - "createdAt": "2026-05-14T00:57:32.245Z", - "updatedAt": "2026-05-15T11:48:58.185Z" + "createdAt": "2026-05-13T13:09:33.788Z", + "updatedAt": "2026-05-16T03:39:49.319Z" } diff --git a/package.json b/package.json index 86ebe4c..bb3f957 100644 --- a/package.json +++ b/package.json @@ -2,7 +2,7 @@ "name": "astra", "displayName": "Astra", "description": "The personal intelligence layer for Antigravity and VS Code. A private cognitive partner for deep project context, memory, and proactive strategic decision-making.", - "version": "2.2.12", + "version": "2.2.13", "publisher": "g1nation", "license": "MIT", "icon": "assets/icon.png", diff --git a/src/sidebarProvider.ts b/src/sidebarProvider.ts index 2054fb4..36eea21 100644 --- a/src/sidebarProvider.ts +++ b/src/sidebarProvider.ts @@ -3873,8 +3873,6 @@ header{display:flex;justify-content:space-between;align-items:center;padding:10p .office:before{content:'';position:absolute;left:0;right:0;top:16%;bottom:0;background-image:linear-gradient(rgba(255,255,255,.028) 1px,transparent 1px),linear-gradient(90deg,rgba(255,255,255,.028) 1px,transparent 1px);background-size:48px 48px} .office:after{content:'';position:absolute;left:0;right:0;top:15.5%;height:8px;background:linear-gradient(180deg,rgba(0,0,0,.36),transparent)} .stage{position:relative;width:720px;height:585px;margin:0} -.zone{position:absolute;border:1px solid rgba(255,255,255,.05);background:rgba(255,255,255,.018);box-shadow:inset 0 1px 0 rgba(255,255,255,.035);border-radius:10px} -.zone.exec{left:220px;top:18px;width:280px;height:150px;background:rgba(124,131,255,.06)}.zone.core{left:28px;top:175px;width:520px;height:170px}.zone.ops{left:28px;top:355px;width:520px;height:170px}.zone.lounge{left:560px;top:355px;width:132px;height:170px;background:rgba(255,189,89,.045)} .wall-window{position:absolute;top:16px;width:86px;height:42px;border:3px solid rgba(206,223,255,.35);background:linear-gradient(180deg,rgba(160,208,255,.3),rgba(110,150,210,.1));box-shadow:inset 0 0 0 2px rgba(15,20,31,.55)} .wall-window.w1{left:84px}.wall-window.w2{left:550px} .obj,.desk,.char{position:absolute;image-rendering:pixelated} @@ -3885,26 +3883,26 @@ header{display:flex;justify-content:space-between;align-items:center;padding:10p @keyframes po-pulse{0%,100%{transform:scale(1);opacity:1}50%{transform:scale(1.5);opacity:.6}} /* ── C. 직군별 페르소나 컬러 ── 책상 outline 가벼운 강조, 활성 캐릭터 위 점이 직군색. data-role attribute로 자동 매핑. 사용자가 PNG sprite로 swap해도 컬러는 유지. */ -.char[data-role="ceo"],.desk[data-role="ceo"] {--role-color:#A78BFA} -.char[data-role="planner"],.desk[data-role="planner"] {--role-color:#60A5FA} -.char[data-role="researcher"],.desk[data-role="researcher"] {--role-color:#10B981} -.char[data-role="designer"],.desk[data-role="designer"] {--role-color:#F472B6} -.char[data-role="developer"],.desk[data-role="developer"] {--role-color:#FBBF24} -.char[data-role="qa"],.desk[data-role="qa"] {--role-color:#22D3EE} -.char[data-role="inspector"],.desk[data-role="inspector"] {--role-color:#FB923C} -.char[data-role="support"],.desk[data-role="support"] {--role-color:#94A3B8} +.char[data-agent="ceo"],.desk[data-agent="ceo"] {--role-color:#A78BFA} +.char[data-agent="planner"],.desk[data-agent="planner"] {--role-color:#60A5FA} +.char[data-agent="researcher"],.desk[data-agent="researcher"] {--role-color:#10B981} +.char[data-agent="designer"],.desk[data-agent="designer"] {--role-color:#F472B6} +.char[data-agent="developer"],.desk[data-agent="developer"] {--role-color:#FBBF24} +.char[data-agent="qa"],.desk[data-agent="qa"] {--role-color:#22D3EE} +.char[data-agent="inspector"],.desk[data-agent="inspector"] {--role-color:#FB923C} +.char[data-agent="support"],.desk[data-agent="support"] {--role-color:#94A3B8} .char.active::after{content:'';position:absolute;left:0;right:0;bottom:-4px;height:3px;background:var(--role-color,var(--accent));box-shadow:0 0 8px var(--role-color,var(--accent));border-radius:2px;animation:po-glow 1.6s ease-in-out infinite} @keyframes po-glow{0%,100%{opacity:.7}50%{opacity:1}} .desk{position:relative} .desk::after{content:'';position:absolute;inset:-2px;border-radius:4px;border:2px solid transparent;pointer-events:none;transition:border-color .3s} -.char.active ~ .desk[data-role],.stage:has(.char.active[data-role="ceo"]) .desk[data-role="ceo"]::after, -.stage:has(.char.active[data-role="planner"]) .desk[data-role="planner"]::after, -.stage:has(.char.active[data-role="researcher"]) .desk[data-role="researcher"]::after, -.stage:has(.char.active[data-role="designer"]) .desk[data-role="designer"]::after, -.stage:has(.char.active[data-role="developer"]) .desk[data-role="developer"]::after, -.stage:has(.char.active[data-role="qa"]) .desk[data-role="qa"]::after, -.stage:has(.char.active[data-role="inspector"]) .desk[data-role="inspector"]::after, -.stage:has(.char.active[data-role="support"]) .desk[data-role="support"]::after +.stage:has(.char.active[data-agent="ceo"]) .desk[data-agent="ceo"]::after, +.stage:has(.char.active[data-agent="planner"]) .desk[data-agent="planner"]::after, +.stage:has(.char.active[data-agent="researcher"]) .desk[data-agent="researcher"]::after, +.stage:has(.char.active[data-agent="designer"]) .desk[data-agent="designer"]::after, +.stage:has(.char.active[data-agent="developer"]) .desk[data-agent="developer"]::after, +.stage:has(.char.active[data-agent="qa"]) .desk[data-agent="qa"]::after, +.stage:has(.char.active[data-agent="inspector"]) .desk[data-agent="inspector"]::after, +.stage:has(.char.active[data-agent="support"]) .desk[data-agent="support"]::after {border-color:var(--role-color)} .shadow{position:absolute;left:12px;bottom:0;width:28px;height:7px;background:radial-gradient(ellipse,rgba(0,0,0,.55),transparent 70%)} .bubble{position:absolute;z-index:20;transform:translate(-50%,-100%);background:#fff;color:#222;padding:5px 8px;border-radius:8px;font-size:11px;box-shadow:2px 2px 0 rgba(0,0,0,.35);white-space:nowrap} @@ -3949,7 +3947,29 @@ body:not([data-edit-mode="true"]) .char{cursor:pointer} .ctx-detail dt{color:#94A3B8;font-weight:600;white-space:nowrap} .ctx-detail dd{margin:0;color:#F1F4FB;overflow-wrap:anywhere} .ctx-detail .cd-logs{margin-top:10px;padding:6px 8px;background:rgba(0,0,0,.3);border-radius:4px;font-family:ui-monospace,monospace;font-size:10.5px;max-height:120px;overflow-y:auto} -.edit-toolbar{display:flex;gap:8px;align-items:center;padding:6px 16px;background:rgba(99,102,241,.18);border-bottom:1px solid rgba(99,102,241,.4);font-size:11px}.edit-toolbar .et-hint{flex:1;color:#D7DBEA}.edit-toolbar button{background:rgba(255,255,255,.12);border:1px solid rgba(255,255,255,.25);color:#F1F4FB;padding:3px 10px;border-radius:4px;cursor:pointer;font-size:11px}.edit-toolbar button:hover{background:rgba(99,102,241,.35)} +.edit-toolbar{display:flex;gap:8px;align-items:center;padding:6px 16px;background:rgba(99,102,241,.18);border-bottom:1px solid rgba(99,102,241,.4);font-size:11px;flex-wrap:wrap}.edit-toolbar .et-hint{flex:1;color:#D7DBEA;min-width:160px}.edit-toolbar button{background:rgba(255,255,255,.12);border:1px solid rgba(255,255,255,.25);color:#F1F4FB;padding:3px 10px;border-radius:4px;cursor:pointer;font-size:11px}.edit-toolbar button:hover{background:rgba(99,102,241,.35)} +.edit-toolbar button.add{background:rgba(16,185,129,.22);border-color:rgba(16,185,129,.55)}.edit-toolbar button.add:hover{background:rgba(16,185,129,.4)} +.edit-toolbar button.del{background:rgba(239,68,68,.22);border-color:rgba(239,68,68,.55)}.edit-toolbar button.del:hover{background:rgba(239,68,68,.4)}.edit-toolbar button[disabled]{opacity:.4;cursor:not-allowed} +/* 선택된 item 의 속성 편집 패널 — 우측 슬라이드 */ +.prop-panel{position:absolute;right:12px;top:90px;width:240px;background:#13162A;border:1px solid #2A2E3F;border-radius:8px;box-shadow:0 8px 24px rgba(0,0,0,.6);padding:12px;font-size:11px;color:#F1F4FB;z-index:25;display:none} +.prop-panel.show{display:block} +.prop-panel h4{margin:0 0 8px;font-size:12px;color:#A78BFA;text-transform:uppercase;letter-spacing:.04em} +.prop-panel .pp-row{margin-bottom:8px} +.prop-panel label{display:block;font-size:10px;color:#94A3B8;margin-bottom:2px} +.prop-panel select,.prop-panel input{width:100%;background:#0c1020;color:#F1F4FB;border:1px solid #2A2E3F;border-radius:4px;padding:3px 6px;font-size:11px} +.prop-panel .pp-thumbs{display:grid;grid-template-columns:repeat(4,1fr);gap:4px;margin-top:4px} +.prop-panel .pp-thumb{width:100%;aspect-ratio:1/1;background:#0c1020;border:1px solid #2A2E3F;border-radius:3px;cursor:pointer;display:flex;align-items:center;justify-content:center;padding:2px} +.prop-panel .pp-thumb img{max-width:100%;max-height:100%;image-rendering:pixelated} +.prop-panel .pp-thumb.active{border-color:#A78BFA;box-shadow:0 0 0 2px rgba(167,139,250,.35)} +/* 프랍 추가 picker — 모달 grid */ +.prop-picker{position:fixed;inset:0;background:rgba(0,0,0,.55);z-index:1100;display:flex;align-items:center;justify-content:center} +.prop-picker-box{background:#13162A;border:1px solid #2A2E3F;border-radius:10px;padding:14px;max-width:520px;max-height:80vh;overflow-y:auto;color:#F1F4FB} +.prop-picker-box h3{margin:0 0 10px;font-size:13px;color:#A78BFA} +.prop-picker-grid{display:grid;grid-template-columns:repeat(5,1fr);gap:8px} +.prop-pick{background:#0c1020;border:1px solid #2A2E3F;border-radius:4px;padding:6px;cursor:pointer;text-align:center} +.prop-pick:hover{border-color:#A78BFA} +.prop-pick img{max-width:60px;max-height:60px;image-rendering:pixelated} +.prop-pick .pp-name{font-size:10px;color:#94A3B8;margin-top:4px;word-break:break-all} /* 편집 모드 — 드래그 가능 요소 강조 */ body[data-edit-mode="true"] .stage{background-image:linear-gradient(rgba(99,102,241,.15) 1px,transparent 1px),linear-gradient(90deg,rgba(99,102,241,.15) 1px,transparent 1px);background-size:32px 32px} body[data-edit-mode="true"] .desk,body[data-edit-mode="true"] .char,body[data-edit-mode="true"] .obj{cursor:grab;outline:1px dashed rgba(99,102,241,.5)} @@ -3963,7 +3983,10 @@ footer{padding:8px 16px 12px;border-top:1px solid rgba(255,255,255,.08);backgrou
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