Release v2.1.8: Company Agent roster overhaul and UI polish
This commit is contained in:
g1nation
@@ -3,15 +3,15 @@
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<!-- ASTRA:AUTO-START -->
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## Snapshot
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- **Workspace**: `ConnectAI` `v2.1.2` _(absolute path varies by environment; resolved from the active VS Code workspace)_
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- **Workspace**: `ConnectAI` `v2.1.8` _(absolute path varies by environment; resolved from the active VS Code workspace)_
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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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- **Stack**: TypeScript, Node.js, VS Code Extension, LM Studio SDK, Test runner
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- **Stats**: 205 source files, ~36,036 lines across 5 top-level modules.
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- **Stats**: 214 source files, ~39,400 lines across 5 top-level modules.
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## Last Refresh
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- **Time**: 2026-05-13T17:43:53.933Z
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- **Files newly analysed**: 0
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- **Files reused from cache**: 205
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- **Time**: 2026-05-14T13:24:53.642Z
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- **Files newly analysed**: 11
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- **Files reused from cache**: 203
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## Directory Map
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```mermaid
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@@ -37,11 +37,11 @@ mindmap
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> Arrows: which top-level module imports from which.
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```mermaid
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flowchart LR
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src["src/<br/>100 files"]
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src["src/<br/>102 files"]
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media["media/<br/>6 files"]
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tests["tests/<br/>27 files"]
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core_py["core_py/<br/>6 files"]
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docs["docs/<br/>66 files"]
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docs["docs/<br/>73 files"]
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tests --> src
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```
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@@ -53,21 +53,21 @@ flowchart LR
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## Hub Files
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> Imported by many other files — touching these has wide blast radius.
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- `src/utils.ts` — referenced by **43** files
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- `src/config.ts` — referenced by **12** files
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- `src/utils.ts` — referenced by **44** files
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- `src/config.ts` — referenced by **13** files
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- `src/lib/paths.ts` — referenced by **10** files
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- `src/features/company/types.ts` — referenced by **9** files · 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
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- `src/features/company/agents.ts` — referenced by **7** files · The 9-agent roster for 1인 기업 모드. Each entry is a static description — persona, role, specialty — used to build the specialist's system prompt at dispatch time. The set was adopted from Connectorigin's
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- `src/features/company/types.ts` — referenced by **10** files · 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
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- `src/retrieval/lessonHelpers.ts` — referenced by **6** files · 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
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- `src/skills/agentKnowledgeMap.ts` — referenced by **6** files
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- `src/lib/engine.ts` — referenced by **6** files
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- `src/core/services.ts` — referenced by **6** files
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## Modules
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### `src/` — 100 files, ~23,874 lines
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### `src/` — 102 files, ~25,874 lines
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**Sub-directories**
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- `src/features/` (28) — The 9-agent roster for 1인 기업 모드. Each entry is a static description — persona, role, specialty — used to build the speci
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- `src/features/` (29) — 기본 에이전트 로스터 — 1인 기업 모드의 출고 디폴트. 설계 의도: 제품 개발 파이프라인(기획 → 디자인 → 개발 → QA → 출시 → 마케팅 → 회고)을 한 사람이 1인 기업으로 운영할 때 필요한 직군을 모두 커
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- `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
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- `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
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- `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
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@@ -77,42 +77,42 @@ flowchart LR
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- `src/lmstudio/` (4) — 4 files (.ts)
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- `src/sidebar/` (4) — 4 files (.ts)
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- `src/skills/` (4) — 4 files (.ts)
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- `src/agents/` (2) — 2 files (.ts)
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- `src/agents/` (3) — Reflection → Lesson persistence Take the Reflector agent's structured critique and persist any substantive findings as a
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- `src/scaffolder/` (2) — Scaffolder template catalog. Templates are pure data — (projectName) => { [relativePath]: contents }. New templates are
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**Key files**
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- `src/utils.ts` (268 lines)
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- `src/config.ts` (216 lines)
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- `src/features/company/types.ts` (150 lines) — 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
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- `src/config.ts` (224 lines)
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- `src/features/company/types.ts` (331 lines) — 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
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- `src/lib/paths.ts` (151 lines)
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- `src/sidebarProvider.ts` (3026 lines)
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- `src/features/company/agents.ts` (136 lines) — The 9-agent roster for 1인 기업 모드. Each entry is a static description — persona, role, specialty — used to build the specialist's system prompt at dispatch time. The set was adopted from Connectorigin's
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- `src/features/company/companyConfig.ts` (877 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
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- `src/sidebarProvider.ts` (3232 lines)
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- `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
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- `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.
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- `src/skills/agentKnowledgeMap.ts` (374 lines)
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- `src/core/services.ts` (164 lines)
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- `src/agent.ts` (3232 lines)
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- `src/features/company/companyConfig.ts` (330 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
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- `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
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- `src/lib/engine.ts` (880 lines)
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- `src/agent.ts` (3232 lines)
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- `src/lib/engine.ts` (906 lines)
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- `src/features/approval/approvalQueue.ts` (129 lines)
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- `src/integrations/telegram/telegramClient.ts` (154 lines)
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- `src/features/company/dispatcher.ts` (631 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
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- `src/features/projectArchitecture/scanner.ts` (644 lines) — 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
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- `src/lib/contextManager.ts` (275 lines) — 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
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- `src/features/company/agents.ts` (184 lines) — 기본 에이전트 로스터 — 1인 기업 모드의 출고 디폴트. 설계 의도: 제품 개발 파이프라인(기획 → 디자인 → 개발 → QA → 출시 → 마케팅 → 회고)을 한 사람이 1인 기업으로 운영할 때 필요한 직군을 모두 커버한다. 각 에이전트는 - name — 직군에 어울리는 한국식 닉네임 - role — 한국어 정식 직함 (어떤 일을 하는 사람인지) - tagl
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- `src/core/astraPath.ts` (50 lines) — 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
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- `src/extension.ts` (966 lines)
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- `src/features/projectChronicle/types.ts` (118 lines)
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- `src/lmstudio/client.ts` (147 lines)
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- `src/retrieval/brainIndex.ts` (325 lines) — 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 <brainPath>/.astra/brain-index.json 에
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- `src/features/company/promptBuilder.ts` (202 lines) — 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 (<createfile>,
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- `src/features/company/sessionStore.ts` (231 lines) — Disk persistence for company-mode session artefacts. Each company turn produces a timestamped directory: <workspaceRoot>/.astra/company/sessions/2026-05-13T21-29/ ├─ brief.md ← CEO's task decompositio
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- `src/features/company/promptBuilder.ts` (231 lines) — 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 (<createfile>,
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### `media/` — 6 files, ~4,099 lines
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### `media/` — 6 files, ~5,337 lines
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**Key files**
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- `media/sidebar.css` (1225 lines) — Stylesheet
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- `media/sidebar.js` (1874 lines)
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- `media/sidebar.html` (356 lines) — Astra
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- `media/sidebar.css` (1450 lines) — Stylesheet
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- `media/sidebar.js` (2791 lines)
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- `media/sidebar.html` (452 lines) — Astra
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- `media/settings-panel.css` (210 lines) — Stylesheet
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- `media/settings-panel.html` (164 lines) — Astra Settings
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- `media/settings-panel.js` (270 lines)
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@@ -160,10 +160,10 @@ flowchart LR
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- `core_py/optimizer.py` (55 lines)
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- `core_py/queue_worker.py` (82 lines)
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### `docs/` — 66 files, ~2,716 lines
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### `docs/` — 73 files, ~2,842 lines
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**Sub-directories**
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- `docs/records/` (54) — Astra Project Chronicle Records
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- `docs/records/` (61) — Astra Project Chronicle Records
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- `docs/docs/` (5) — docs Chronicle Records
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**Key files**
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@@ -220,7 +220,7 @@ flowchart LR
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- `g1nation.company.toggle` — Astra: Toggle 1인 기업 Mode
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- `g1nation.company.manage` — Astra: Manage 1인 기업 Agents
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- `g1nation.company.openSessions` — Astra: Open 1인 기업 Sessions Folder
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- **Configuration** (39 settings):
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- **Configuration** (40 settings):
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- `g1nation.multiAgentEnabled` *(boolean)* _(default: `false`)_ — Enable Multi-Agent Workflow (Planner -> Researcher -> Writer) for complex tasks.
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- `g1nation.memoryEnabled` *(boolean)* _(default: `true`)_ — Enable layered memory injection before each model response.
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- `g1nation.memoryShortTermMessages` *(number)* _(default: `8`)_ — Number of recent conversation messages included as short-term memory.
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@@ -260,6 +260,7 @@ flowchart LR
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- `g1nation.embeddingBlendAlpha` *(number)* _(default: `0.5`)_ — Hybrid score blend: 0 = pure TF-IDF (sparse / keyword), 1 = pure embedding cosine (dense / semantic), 0.5 = balanced. Only used when g1nation.embeddingModel is set. Default 0.5.
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- `g1nation.knowledgeMix.secondBrainWeight` *(number)* _(default: `50`)_ — Knowledge Mix (0–100): how heavily the assistant should lean on Second Brain evidence vs. its own general knowledge. 0 = Second Brain disabled (model knowledge only). 50 = balanced (legacy default). 1
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- `g1nation.enableReflection` *(boolean)* _(default: `true`)_ — Insert a Self-Reflection (Reflector) stage between Researcher and Writer in the multi-agent workflow. The Reflector critically reviews the plan and research output (gaps, contradictions, unsupported c
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- `g1nation.autoLessonFromReflection` *(boolean)* _(default: `true`)_ — 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 pipe
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## Dependencies
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- **Runtime** (2): `@lmstudio/sdk`, `pdf-parse`
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@@ -307,7 +308,7 @@ Astra는 대표님의 명시적인 승인 하에 로컬 시스템의 강력한
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**Designed for High-Performance Decision Making.**
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Copyright (C) **g1nation**. All rights reserved.
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_Last auto-scan: 2026-05-13T17:43:53.933Z · signature `5020e02c`_
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_Last auto-scan: 2026-05-14T13:24:53.642Z · signature `f554c52a`_
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<!-- ASTRA:AUTO-END -->
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## Purpose
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@@ -1,6 +1,6 @@
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{
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"version": 1,
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"generatedAt": "2026-05-13T17:43:53.948Z",
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"generatedAt": "2026-05-14T13:24:53.652Z",
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"files": {
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"src/agent.ts": {
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"mtimeMs": 1778683690000,
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@@ -58,6 +58,16 @@
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"src/lib/engine"
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]
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},
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"src/agents/reflectionPersister.ts": {
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"mtimeMs": 1778763469000,
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||||
"size": 11986,
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||||
"lines": 308,
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"role": "Reflection → Lesson persistence Take the Reflector agent's structured critique and persist any substantive findings as a lesson card in <brainDir>/lessons/auto-reflector/. The existing brain retrieval",
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"imports": [
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"src/utils",
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"src/retrieval/lessonHelpers"
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]
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},
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"src/bridge.ts": {
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||||
"mtimeMs": 1778681774000,
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||||
"size": 9705,
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||||
@@ -72,9 +82,9 @@
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]
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||||
},
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||||
"src/config.ts": {
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||||
"lines": 224,
|
||||
"role": "",
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||||
"imports": []
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},
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@@ -312,23 +322,22 @@
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]
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||||
},
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"src/features/company/agents.ts": {
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||||
"mtimeMs": 1778680824000,
|
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"size": 6684,
|
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"lines": 136,
|
||||
"role": "The 9-agent roster for 1인 기업 모드. Each entry is a static description — persona, role, specialty — used to build the specialist's system prompt at dispatch time. The set was adopted from Connectorigin's",
|
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"mtimeMs": 1778764697000,
|
||||
"size": 11623,
|
||||
"lines": 184,
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||||
"role": "기본 에이전트 로스터 — 1인 기업 모드의 출고 디폴트. 설계 의도: 제품 개발 파이프라인(기획 → 디자인 → 개발 → QA → 출시 → 마케팅 → 회고)을 한 사람이 1인 기업으로 운영할 때 필요한 직군을 모두 커버한다. 각 에이전트는 - name — 직군에 어울리는 한국식 닉네임 - role — 한국어 정식 직함 (어떤 일을 하는 사람인지) - tagl",
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"imports": [
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"src/features/company/types"
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]
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},
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"src/features/company/ceoPlanner.ts": {
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"mtimeMs": 1778762677000,
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"size": 11307,
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"lines": 266,
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"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",
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"imports": [
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"src/core/services",
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"src/utils",
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"src/features/company/agents",
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"src/features/company/companyConfig",
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"src/features/company/promptAssets",
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"src/features/company/promptBuilder",
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@@ -336,22 +345,22 @@
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]
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},
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"src/features/company/ceoReporter.ts": {
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"mtimeMs": 1778762677000,
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"size": 4895,
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||||
"lines": 122,
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"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",
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"imports": [
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"src/core/services",
|
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"src/utils",
|
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"src/features/company/agents",
|
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"src/features/company/companyConfig",
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"src/features/company/promptAssets",
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"src/features/company/types"
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]
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||||
},
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||||
"src/features/company/companyConfig.ts": {
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"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",
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||||
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||||
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||||
@@ -359,9 +368,9 @@
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"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",
|
||||
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|
||||
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|
||||
@@ -369,7 +378,6 @@
|
||||
"src/skills/scopedBrainRetriever",
|
||||
"src/skills/agentKnowledgeMap",
|
||||
"src/retrieval/knowledgeMix",
|
||||
"src/features/company/agents",
|
||||
"src/features/company/companyConfig",
|
||||
"src/features/company/ceoPlanner",
|
||||
"src/features/company/ceoReporter",
|
||||
@@ -380,18 +388,28 @@
|
||||
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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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||||
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"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",
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|
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"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 (<createfile>, ",
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||||
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|
||||
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|
||||
@@ -442,22 +460,22 @@
|
||||
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"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",
|
||||
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|
||||
"src/utils",
|
||||
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|
||||
"src/integrations/telegram/conversationHistory",
|
||||
"src/features/company/agents",
|
||||
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|
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"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",
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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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|
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@@ -945,7 +965,8 @@
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||||
"src/features/projectArchitecture",
|
||||
"src/features/projectArchitecture/intentDetector",
|
||||
"src/features/company",
|
||||
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|
||||
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|
||||
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|
||||
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@@ -1021,8 +1042,8 @@
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@@ -1507,8 +1528,29 @@
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"role": "Bug: 문제점을 읽고 어떻게 개선하는게 최선인지 분석해주면 좋겠어. 알겠습니다. 지금부터 ConnectAI 프로젝트에만 완전히 집중하겠습니다. ...",
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"role": "Bug: 질문이 있어. 논문을 쓰려고해. 논문 주제는 서비스적이 아닌 사용자가 ai에게 구조로 질문을 해야 사용자의 의도에 맞는 답변을 받을 수 있을까야...",
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||||
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||||
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"docs/records/ConnectAI/bugs/BUG-0013-thesis-paper를-쓰려고-하는데-아래와-같이-쓰면-좋을까-이런-식으로-쓰면-되지-않을까-싶음-1-in.md": {
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"role": "Bug: Thesis paper를 쓰려고 하는데 아래와 같이 쓰면 좋을까? 이런 식으로 쓰면 되지 않을까 싶음 1. Introduction Thesis ...",
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||||
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"docs/records/ConnectAI/bugs/BUG-0014-논문-outline-title-인간-ai-상호작용에서-의도-정렬을-높이기-위한-최소-질의-구조-연구-또는-사.md": {
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"role": "Bug: 논문 Outline Title 인간-AI 상호작용에서 의도 정렬을 높이기 위한 최소 질의 구조 연구 또는 사용자의 인지적 편향을 보완하는 구조화...",
|
||||
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@@ -1584,6 +1626,20 @@
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||||
"role": "ADR: /Volumes/Data/project/Antigravity/ConnectAI self reflection 기능이 적용되었는지 확인해줘. 1인 ...",
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"role": "ADR: E:\\Wiki\\connectai self reflection 기능이 있는데 어떻게 SELF REFLECTION이 반영되는지 분석해줘.",
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||||
"imports": []
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||||
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|
||||
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"role": "ADR: E:\\Wiki\\connectai self reflection 기능이 있는데 어떻게 SELF REFLECTION이 반영되는지 분석해줘.",
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@@ -1724,6 +1780,13 @@
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"role": "Development Log: 너는 분석 요청하거나 내가 작업 요청을 할때 connectai architecture.md 문서를 참고하고 작업을 하나?",
|
||||
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||||
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|
||||
"docs/records/ConnectAI/development/2026-05-14_reflector-에이전트가-1인-기업-에이전트-목록에는-안보이는데_implementation.md": {
|
||||
"mtimeMs": 1778762677000,
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"role": "Development Log: REFLECTOR 에이전트가 1인 기업 에이전트 목록에는 안보이는데",
|
||||
"imports": []
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||||
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||||
"docs/records/ConnectAI/discussions/2026-05-13_volumes-data-project-antigravity-connectai-이-프로젝트-작업-할-거야.md": {
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"mtimeMs": 1778690673000,
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@@ -1752,6 +1815,13 @@
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"role": "Discussion: /Volumes/Data/project/Antigravity/ConnectAI 이 프로젝트를 작업할거야.",
|
||||
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|
||||
},
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||||
"docs/records/ConnectAI/discussions/2026-05-14_최성연-알아-칼리버스에서-근무한데.md": {
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"role": "Discussion: 최성연 알아? 칼리버스에서 근무한데",
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|
||||
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@@ -1795,7 +1865,7 @@
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"role": "Project Timeline",
|
||||
|
||||
+1
-1
@@ -1,5 +1,5 @@
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{
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||||
"result": "Final report with inconsistencies. This should be long enough to pass validation.",
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||||
"createdAt": 1778749506862,
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"createdAt": 1778765114489,
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}
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+1
-1
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{
|
||||
"result": "[CONFLICT WARNING] 성능이 200% 증가했습니다. vs 그러나 동시에 50% 감소했습니다. 최적화와 성능 저하가 동시에 발견됨.",
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"createdAt": 1778749506860,
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"createdAt": 1778765114485,
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"modelVersion": "unknown"
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+1
-1
@@ -1,5 +1,5 @@
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{
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||||
"result": "Detailed Execution Plan: 1. Research 2. Analyze 3. Write report with high quality.",
|
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"createdAt": 1778749506858,
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+2
-2
@@ -1,5 +1,5 @@
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{
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"result": "---\nid: stress_conflict_1778749506840\ndate: 2026-05-14T09:05:06.864Z\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... (17ms)\n- **[RESEARCHER]** 핵심 정보 수집 및 분석 중... (2ms)\n- **[WRITER]** 최종 리포트 작성 및 편집 중... (2ms)\n",
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"createdAt": 1778749506864,
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"result": "---\nid: stress_conflict_1778765114471\ndate: 2026-05-14T13:25:14.493Z\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... (10ms)\n- **[RESEARCHER]** 핵심 정보 수집 및 분석 중... (4ms)\n- **[WRITER]** 최종 리포트 작성 및 편집 중... (4ms)\n",
|
||||
"createdAt": 1778765114493,
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||||
}
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+10
-10
@@ -1,8 +1,8 @@
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||||
{
|
||||
"missionId": "stress_conflict_1778749506840",
|
||||
"missionId": "stress_conflict_1778765114471",
|
||||
"status": "completed",
|
||||
"startTime": "2026-05-14T09:05:06.840Z",
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"results": {
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||||
"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": 17,
|
||||
"durationMs": 10,
|
||||
"message": "전략 수립 중...",
|
||||
"ts": "2026-05-14T09:05:06.857Z"
|
||||
"ts": "2026-05-14T13:25:14.481Z"
|
||||
},
|
||||
{
|
||||
"from": "planner",
|
||||
"to": "researcher",
|
||||
"durationMs": 2,
|
||||
"durationMs": 4,
|
||||
"message": "핵심 정보 수집 및 분석 중...",
|
||||
"ts": "2026-05-14T09:05:06.859Z"
|
||||
"ts": "2026-05-14T13:25:14.485Z"
|
||||
},
|
||||
{
|
||||
"from": "researcher",
|
||||
"to": "writer",
|
||||
"durationMs": 2,
|
||||
"durationMs": 4,
|
||||
"message": "최종 리포트 작성 및 편집 중...",
|
||||
"ts": "2026-05-14T09:05:06.861Z"
|
||||
"ts": "2026-05-14T13:25:14.489Z"
|
||||
},
|
||||
{
|
||||
"from": "writer",
|
||||
"to": "completed",
|
||||
"durationMs": 4,
|
||||
"message": "미션 완료",
|
||||
"ts": "2026-05-14T09:05:06.865Z"
|
||||
"ts": "2026-05-14T13:25:14.493Z"
|
||||
}
|
||||
],
|
||||
"resilienceMetrics": {
|
||||
Reference in New Issue
Block a user