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+# AI News Phase 1 — articles Source Implementation Plan
+
+> **For agentic workers:** REQUIRED SUB-SKILL: Use superpowers:subagent-driven-development (recommended) or superpowers:executing-plans to implement this plan task-by-task. Steps use checkbox (`- [ ]`) syntax for tracking.
+
+**Goal:** ai_news 파이프라인의 데이터 소스를 Naver 스크래퍼에서 기존 `articles` 테이블로 교체. 종목명 substring 매핑으로 시총 상위 100 ticker 의 뉴스 sentiment 산출. `news_sentiment.source` 컬럼 추가로 Phase 2 비교 baseline 확보.
+
+**Architecture:** 신규 `articles_source.py` 모듈이 `articles` 테이블 + `krx_master.name` substring 매핑으로 ticker별 뉴스 dict 반환. `pipeline.py`는 scraper 호출 대신 articles_source 사용. `analyzer.py` 가 LLM prompt 에 `summary` 포함. 텔레그램 메시지에 매핑 hit-rate 라인 추가. legacy `scraper.py` 는 deprecate 주석만 추가하고 보존.
+
+**Tech Stack:** Python 3.11 / SQLite (WAL + busy_timeout) / anthropic AsyncClient / FastAPI / pytest + pytest-asyncio.
+
+**선행 spec**: `web-ui/docs/superpowers/specs/2026-05-14-ai-news-articles-source-design.md`
+
+---
+
+## 파일 구조
+
+신규 파일 (backend):
+```
+web-backend/stock-lab/app/screener/ai_news/
+  articles_source.py             ← DB articles 조회 + 종목명 매핑
+
+web-backend/stock-lab/tests/
+  test_ai_news_articles_source.py    ← 6 tests
+```
+
+수정 파일 (backend):
+```
+web-backend/stock-lab/app/screener/
+  schema.py                      ← news_sentiment.source 컬럼 + migration
+  ai_news/pipeline.py            ← articles_source 사용, _make_http 제거
+  ai_news/analyzer.py            ← prompt에 summary/pub_date 포함
+  ai_news/telegram.py            ← build_message 에 mapping 라인
+  ai_news/scraper.py             ← deprecate 주석만 추가
+  router.py                      ← post_refresh_news_sentiment 에 mapping 전달
+
+web-backend/stock-lab/tests/
+  test_ai_news_pipeline.py       ← articles_source mock 으로 갱신
+  test_ai_news_analyzer.py       ← summary 케이스 추가
+  test_ai_news_telegram.py       ← mapping 인자 케이스 추가
+  test_ai_news_router.py         ← mapping 응답 필드 검증
+```
+
+---
+
+### Task 1: schema.py — `news_sentiment.source` 컬럼 + migration
+
+**Files:**
+- Modify: `web-backend/stock-lab/app/screener/schema.py`
+
+- [ ] **Step 1: DDL 본문에 `source` 컬럼 정의 추가**
+
+`schema.py` 의 `DDL` 문자열 안 `news_sentiment` 테이블 정의에 `source` 컬럼을 `model` 컬럼 다음에 추가:
+```sql
+CREATE TABLE IF NOT EXISTS news_sentiment (
+  ticker          TEXT NOT NULL,
+  date            TEXT NOT NULL,
+  score_raw       REAL NOT NULL,
+  reason          TEXT NOT NULL DEFAULT '',
+  news_count      INTEGER NOT NULL DEFAULT 0,
+  tokens_input    INTEGER NOT NULL DEFAULT 0,
+  tokens_output   INTEGER NOT NULL DEFAULT 0,
+  model           TEXT NOT NULL DEFAULT 'claude-haiku-4-5-20251001',
+  source          TEXT NOT NULL DEFAULT 'articles',
+  created_at      TEXT NOT NULL DEFAULT (datetime('now','localtime')),
+  PRIMARY KEY (ticker, date)
+);
+```
+
+- [ ] **Step 2: `ensure_screener_schema()` 함수에 1회성 migration 블록 추가**
+
+기존 ai_news weight migration 블록 (라인 ~142-156 근처) 직전 또는 직후에 다음을 추가:
+```python
+    # news_sentiment.source 컬럼 1회 추가 (기존 운영 환경)
+    cols = {r[1] for r in conn.execute(
+        "PRAGMA table_info(news_sentiment)"
+    ).fetchall()}
+    if "source" not in cols:
+        conn.execute(
+            "ALTER TABLE news_sentiment "
+            "ADD COLUMN source TEXT NOT NULL DEFAULT 'articles'"
+        )
+```
+
+위치는 `executescript(DDL)` 직후, 기존 ai_news weight migration block 안이 자연스러움.
+
+- [ ] **Step 3: 기존 schema 테스트 회귀**
+
+```bash
+cd C:\Users\jaeoh\Desktop\workspace\web-backend\stock-lab
+python -m pytest app/test_screener_schema.py -v
+```
+Expected: PASS — 3 tests passed (migration 추가에도 idempotency 유지).
+
+- [ ] **Step 4: Commit**
+
+```bash
+git add app/screener/schema.py
+git commit -m "feat(ai_news): add news_sentiment.source column with migration"
+```
+
+---
+
+### Task 2: `articles_source.py` — DB 매핑 모듈 + 6 tests
+
+**Files:**
+- Create: `web-backend/stock-lab/app/screener/ai_news/articles_source.py`
+- Test: `web-backend/stock-lab/tests/test_ai_news_articles_source.py`
+
+- [ ] **Step 1: 실패하는 테스트 작성**
+
+`tests/test_ai_news_articles_source.py`:
+```python
+import datetime as dt
+import sqlite3
+import pytest
+
+from app.screener.ai_news import articles_source
+from app.screener.schema import ensure_screener_schema
+
+
+@pytest.fixture
+def conn():
+    c = sqlite3.connect(":memory:")
+    c.row_factory = sqlite3.Row
+    ensure_screener_schema(c)
+    # krx_master + articles 시드 helper 는 각 테스트에서 진행
+    yield c
+    c.close()
+
+
+def _seed_master(conn, ticker, name):
+    conn.execute(
+        "INSERT INTO krx_master (ticker, name, market, market_cap, updated_at) "
+        "VALUES (?, ?, 'KOSPI', 1_000_000_000, datetime('now'))",
+        (ticker, name),
+    )
+
+
+def _seed_article(conn, title, summary="", crawled_at="2026-05-14T07:30:00"):
+    import hashlib
+    h = hashlib.md5(f"{title}|x".encode()).hexdigest()
+    conn.execute(
+        "INSERT INTO articles (hash, title, summary, link, press, pub_date, crawled_at) "
+        "VALUES (?, ?, ?, '', '', '2026-05-14', ?)",
+        (h, title, summary, crawled_at),
+    )
+
+
+ASOF = dt.date(2026, 5, 14)
+
+
+def test_single_ticker_match_in_title(conn):
+    _seed_master(conn, "005930", "삼성전자")
+    _seed_article(conn, "삼성전자, HBM 양산 가시화")
+    conn.commit()
+    out, stats = articles_source.gather_articles_for_tickers(
+        conn, ["005930"], ASOF, window_days=1, max_per_ticker=5,
+    )
+    assert len(out["005930"]) == 1
+    assert out["005930"][0]["title"] == "삼성전자, HBM 양산 가시화"
+    assert stats["matched_pairs"] == 1
+    assert stats["hit_tickers"] == 1
+
+
+def test_single_ticker_match_in_summary(conn):
+    _seed_master(conn, "005930", "삼성전자")
+    _seed_article(conn, "메모리 시장 회복세", summary="삼성전자가 1분기 어닝 서프라이즈")
+    conn.commit()
+    out, _ = articles_source.gather_articles_for_tickers(
+        conn, ["005930"], ASOF, window_days=1, max_per_ticker=5,
+    )
+    assert len(out["005930"]) == 1
+
+
+def test_multi_ticker_match(conn):
+    _seed_master(conn, "005930", "삼성전자")
+    _seed_master(conn, "000660", "SK하이닉스")
+    _seed_article(conn, "삼성전자와 SK하이닉스, 메모리 양산 경쟁")
+    conn.commit()
+    out, stats = articles_source.gather_articles_for_tickers(
+        conn, ["005930", "000660"], ASOF, window_days=1, max_per_ticker=5,
+    )
+    assert len(out["005930"]) == 1
+    assert len(out["000660"]) == 1
+    assert stats["matched_pairs"] == 2
+    assert stats["hit_tickers"] == 2
+
+
+def test_no_match_returns_empty_list(conn):
+    _seed_master(conn, "005930", "삼성전자")
+    _seed_article(conn, "엔비디아 실적 발표", summary="AI 칩 수요 견조")
+    conn.commit()
+    out, stats = articles_source.gather_articles_for_tickers(
+        conn, ["005930"], ASOF, window_days=1, max_per_ticker=5,
+    )
+    assert out["005930"] == []
+    assert stats["matched_pairs"] == 0
+    assert stats["hit_tickers"] == 0
+
+
+def test_max_per_ticker_caps_results(conn):
+    _seed_master(conn, "005930", "삼성전자")
+    for i in range(6):
+        _seed_article(conn, f"삼성전자 뉴스 #{i}", crawled_at=f"2026-05-14T0{i}:00:00")
+    conn.commit()
+    out, _ = articles_source.gather_articles_for_tickers(
+        conn, ["005930"], ASOF, window_days=1, max_per_ticker=5,
+    )
+    assert len(out["005930"]) == 5
+
+
+def test_window_days_filters_old_articles(conn):
+    _seed_master(conn, "005930", "삼성전자")
+    _seed_article(conn, "삼성전자 최신 뉴스", crawled_at="2026-05-14T07:00:00")
+    _seed_article(conn, "삼성전자 오래된 뉴스", crawled_at="2026-05-01T07:00:00")
+    conn.commit()
+    out, _ = articles_source.gather_articles_for_tickers(
+        conn, ["005930"], ASOF, window_days=1, max_per_ticker=5,
+    )
+    assert len(out["005930"]) == 1
+    assert "최신" in out["005930"][0]["title"]
+```
+
+- [ ] **Step 2: 테스트 실패 확인**
+
+```bash
+python -m pytest tests/test_ai_news_articles_source.py -v
+```
+Expected: FAIL — "No module named 'app.screener.ai_news.articles_source'".
+
+- [ ] **Step 3: `articles_source.py` 구현** — 정확히:
+
+```python
+"""기존 articles 테이블에서 종목별 뉴스 매핑."""
+
+from __future__ import annotations
+
+import datetime as dt
+import logging
+import sqlite3
+from typing import Any, Dict, List, Tuple
+
+log = logging.getLogger(__name__)
+
+
+def gather_articles_for_tickers(
+    conn: sqlite3.Connection,
+    tickers: List[str],
+    asof: dt.date,
+    *,
+    window_days: int = 1,
+    max_per_ticker: int = 5,
+) -> Tuple[Dict[str, List[Dict[str, Any]]], Dict[str, int]]:
+    """articles 에서 ticker.name substring 매칭으로 종목별 뉴스 dict 반환.
+
+    Returns:
+        (
+          {ticker: [{"title": str, "summary": str, "press": str, "pub_date": str}, ...]},
+          {"total_articles": int, "matched_pairs": int, "hit_tickers": int},
+        )
+    """
+    out: Dict[str, List[Dict[str, Any]]] = {t: [] for t in tickers}
+    stats = {"total_articles": 0, "matched_pairs": 0, "hit_tickers": 0}
+
+    if not tickers:
+        return out, stats
+
+    cutoff = (asof - dt.timedelta(days=window_days)).isoformat()
+
+    placeholders = ",".join("?" * len(tickers))
+    name_rows = conn.execute(
+        f"SELECT ticker, name FROM krx_master WHERE ticker IN ({placeholders})",
+        tickers,
+    ).fetchall()
+    # 2글자 미만 회사명은 false positive 위험으로 제외
+    name_map = {r[0]: r[1] for r in name_rows if r[1] and len(r[1]) >= 2}
+
+    articles = conn.execute(
+        "SELECT title, summary, press, pub_date, crawled_at "
+        "FROM articles WHERE crawled_at >= ? ORDER BY crawled_at DESC",
+        (cutoff,),
+    ).fetchall()
+    stats["total_articles"] = len(articles)
+
+    for a in articles:
+        title = (a[0] or "").strip()
+        summary = (a[1] or "").strip()
+        haystack = title + " " + summary
+        for ticker, name in name_map.items():
+            if name not in haystack:
+                continue
+            if len(out[ticker]) >= max_per_ticker:
+                continue
+            out[ticker].append({
+                "title": title,
+                "summary": summary,
+                "press": a[2] or "",
+                "pub_date": a[3] or "",
+            })
+            stats["matched_pairs"] += 1
+
+    stats["hit_tickers"] = sum(1 for arts in out.values() if arts)
+    return out, stats
+```
+
+- [ ] **Step 4: 테스트 통과 확인**
+
+```bash
+python -m pytest tests/test_ai_news_articles_source.py -v
+```
+Expected: PASS — 6 tests passed.
+
+- [ ] **Step 5: Commit**
+
+```bash
+git add app/screener/ai_news/articles_source.py tests/test_ai_news_articles_source.py
+git commit -m "feat(ai_news): articles_source module (substring ticker matching)"
+```
+
+---
+
+### Task 3: `analyzer.py` — prompt 에 summary/pub_date 포함
+
+**Files:**
+- Modify: `web-backend/stock-lab/app/screener/ai_news/analyzer.py`
+- Modify: `web-backend/stock-lab/tests/test_ai_news_analyzer.py`
+
+- [ ] **Step 1: 테스트 갱신 (실패 유도)**
+
+`tests/test_ai_news_analyzer.py` 의 `NEWS` 상수와 `test_score_sentiment_success_parses_json` 테스트를 다음으로 교체/보강:
+```python
+NEWS = [
+    {"title": "삼성전자, HBM 양산", "summary": "1분기 영업이익 사상 최대", "pub_date": "2026-05-14"},
+    {"title": "메모리 가격 반등", "summary": "", "pub_date": "2026-05-14"},
+]
+
+
+@pytest.mark.asyncio
+async def test_score_sentiment_includes_summary_in_prompt():
+    """summary 가 있으면 prompt 에 포함, 없으면 title 만."""
+    llm = _mk_llm(json.dumps({"score": 5.0, "reason": "ok"}))
+    await analyzer.score_sentiment(llm, "005930", NEWS, name="삼성전자")
+    # mock 의 messages.create 호출 인자 확인
+    call = llm.messages.create.call_args
+    user_msg = call.kwargs["messages"][0]["content"]
+    assert "1분기 영업이익 사상 최대" in user_msg  # summary 포함
+    assert "삼성전자, HBM 양산" in user_msg  # title 포함
+    assert "2026-05-14" in user_msg  # pub_date 포함
+```
+
+- [ ] **Step 2: 테스트 실행으로 실패 확인**
+
+```bash
+python -m pytest tests/test_ai_news_analyzer.py::test_score_sentiment_includes_summary_in_prompt -v
+```
+Expected: FAIL — `1분기 영업이익 사상 최대` 가 prompt 에 없음.
+
+- [ ] **Step 3: `analyzer.py` 의 news_block 빌더 분리 + summary 포함**
+
+기존 prompt 빌드 부분 수정. `score_sentiment` 함수의 prompt build 직전에 helper 함수 추가:
+
+```python
+def _format_news_block(news: List[Dict[str, Any]]) -> str:
+    """news dict 리스트 → prompt 에 들어가는 텍스트 블록.
+
+    summary 가 있으면 title 다음 줄에 indent 해서 포함 (최대 200자).
+    pub_date 가 있으면 title 앞에 표시.
+    """
+    lines: List[str] = []
+    for n in news:
+        date = (n.get("pub_date") or "").strip()
+        title = (n.get("title") or "").strip()
+        summary = (n.get("summary") or "").strip()
+        prefix = f"[{date}] " if date else ""
+        if summary:
+            lines.append(f"- {prefix}{title}\n  {summary[:200]}")
+        else:
+            lines.append(f"- {prefix}{title}")
+    return "\n".join(lines)
+```
+
+그리고 `score_sentiment` 안 `news_block` 계산 라인을 다음으로 교체:
+```python
+    news_block = _format_news_block(news)
+```
+
+- [ ] **Step 4: 테스트 통과 확인**
+
+```bash
+python -m pytest tests/test_ai_news_analyzer.py -v
+```
+Expected: PASS — 5 tests (기존 4 + 신규 1) 모두 통과.
+
+- [ ] **Step 5: Commit**
+
+```bash
+git add app/screener/ai_news/analyzer.py tests/test_ai_news_analyzer.py
+git commit -m "feat(ai_news): include summary + pub_date in LLM prompt"
+```
+
+---
+
+### Task 4: `pipeline.py` — articles_source 사용으로 교체
+
+**Files:**
+- Modify: `web-backend/stock-lab/app/screener/ai_news/pipeline.py`
+- Modify: `web-backend/stock-lab/tests/test_ai_news_pipeline.py`
+
+- [ ] **Step 1: 테스트 갱신 (실패 유도)**
+
+`tests/test_ai_news_pipeline.py` 의 `test_refresh_daily_happy_path` 를 다음으로 교체:
+```python
+@pytest.mark.asyncio
+async def test_refresh_daily_happy_path(conn):
+    """3종목 mini integration — articles_source mock + analyzer mock.
+
+    각 종목에 매핑되는 articles 1개씩 있다고 가정.
+    """
+    asof = dt.date(2026, 5, 13)
+
+    fake_articles_by_ticker = {
+        "005930": [{"title": "삼성 뉴스", "summary": "", "press": "", "pub_date": ""}],
+        "000660": [{"title": "SK 뉴스", "summary": "", "press": "", "pub_date": ""}],
+        "373220": [{"title": "LG 뉴스", "summary": "", "press": "", "pub_date": ""}],
+    }
+    fake_stats = {"total_articles": 3, "matched_pairs": 3, "hit_tickers": 3}
+
+    scores_by_ticker = {
+        "005930": 7.5, "000660": 4.0, "373220": -6.0,
+    }
+    async def fake_score(llm, ticker, news, *, name=None, model="m"):
+        return {
+            "ticker": ticker, "score_raw": scores_by_ticker[ticker],
+            "reason": f"r{ticker}", "news_count": 1,
+            "tokens_input": 100, "tokens_output": 20, "model": model,
+        }
+
+    with patch.object(pipeline, "articles_source") as mas, \
+         patch.object(pipeline, "_analyzer") as ma, \
+         patch.object(pipeline, "_make_llm") as ml:
+        mas.gather_articles_for_tickers = MagicMock(
+            return_value=(fake_articles_by_ticker, fake_stats)
+        )
+        ma.score_sentiment = fake_score
+        ml.return_value.__aenter__.return_value = AsyncMock()
+        ml.return_value.__aexit__.return_value = None
+        result = await pipeline.refresh_daily(conn, asof, concurrency=3)
+
+    assert result["asof"] == "2026-05-13"
+    assert result["updated"] == 3
+    assert result["failures"] == []
+    assert result["top_pos"][0]["ticker"] == "005930"
+    assert result["top_neg"][0]["ticker"] == "373220"
+    assert result["mapping"] == fake_stats
+
+    rows = conn.execute("SELECT ticker, score_raw, source FROM news_sentiment "
+                        "WHERE date=?", ("2026-05-13",)).fetchall()
+    assert len(rows) == 3
+    assert all(r["source"] == "articles" for r in rows)
+
+
+@pytest.mark.asyncio
+async def test_refresh_daily_no_match_ticker_skipped(conn):
+    """매핑 0인 ticker 는 LLM 호출 skip + news_sentiment 행 미생성."""
+    asof = dt.date(2026, 5, 13)
+
+    fake_articles_by_ticker = {
+        "005930": [{"title": "삼성", "summary": "", "press": "", "pub_date": ""}],
+        "000660": [],  # 매핑 없음
+        "373220": [],  # 매핑 없음
+    }
+    fake_stats = {"total_articles": 1, "matched_pairs": 1, "hit_tickers": 1}
+
+    async def fake_score(llm, ticker, news, *, name=None, model="m"):
+        return {
+            "ticker": ticker, "score_raw": 5.0, "reason": "r",
+            "news_count": 1, "tokens_input": 100, "tokens_output": 20,
+            "model": model,
+        }
+
+    with patch.object(pipeline, "articles_source") as mas, \
+         patch.object(pipeline, "_analyzer") as ma, \
+         patch.object(pipeline, "_make_llm") as ml:
+        mas.gather_articles_for_tickers = MagicMock(
+            return_value=(fake_articles_by_ticker, fake_stats)
+        )
+        ma.score_sentiment = fake_score
+        ml.return_value.__aenter__.return_value = AsyncMock()
+        ml.return_value.__aexit__.return_value = None
+        result = await pipeline.refresh_daily(conn, asof, concurrency=3)
+
+    assert result["updated"] == 1
+    rows = conn.execute("SELECT ticker FROM news_sentiment "
+                        "WHERE date=?", ("2026-05-13",)).fetchall()
+    assert {r["ticker"] for r in rows} == {"005930"}
+```
+
+기존 `test_refresh_daily_failures_isolated` 는 articles_source 매핑 데이터를 추가해야 함:
+```python
+@pytest.mark.asyncio
+async def test_refresh_daily_failures_isolated(conn):
+    asof = dt.date(2026, 5, 13)
+
+    fake_articles_by_ticker = {
+        "005930": [{"title": "h", "summary": "", "press": "", "pub_date": ""}],
+        "000660": [{"title": "h", "summary": "", "press": "", "pub_date": ""}],
+        "373220": [{"title": "h", "summary": "", "press": "", "pub_date": ""}],
+    }
+    fake_stats = {"total_articles": 3, "matched_pairs": 3, "hit_tickers": 3}
+
+    async def fake_score(llm, ticker, news, *, name=None, model="m"):
+        if ticker == "000660":
+            raise RuntimeError("llm exploded")
+        return {
+            "ticker": ticker, "score_raw": 5.0, "reason": "r", "news_count": 1,
+            "tokens_input": 100, "tokens_output": 20, "model": model,
+        }
+
+    with patch.object(pipeline, "articles_source") as mas, \
+         patch.object(pipeline, "_analyzer") as ma, \
+         patch.object(pipeline, "_make_llm") as ml:
+        mas.gather_articles_for_tickers = MagicMock(
+            return_value=(fake_articles_by_ticker, fake_stats)
+        )
+        ma.score_sentiment = fake_score
+        ml.return_value.__aenter__.return_value = AsyncMock()
+        ml.return_value.__aexit__.return_value = None
+        result = await pipeline.refresh_daily(conn, asof, concurrency=3)
+
+    assert result["updated"] == 2
+    assert len(result["failures"]) == 1
+```
+
+상단 import 에 `MagicMock` 추가 확인:
+```python
+from unittest.mock import AsyncMock, MagicMock, patch
+```
+
+- [ ] **Step 2: 테스트 실패 확인**
+
+```bash
+python -m pytest tests/test_ai_news_pipeline.py -v
+```
+Expected: FAIL — pipeline 이 articles_source 를 아직 사용 안 함.
+
+- [ ] **Step 3: `pipeline.py` 본문 교체**
+
+`pipeline.py` 의 다음을 변경:
+
+(1) 상단 import 에 articles_source 추가:
+```python
+from . import scraper as _scraper          # legacy, kept for backward import
+from . import analyzer as _analyzer
+from . import articles_source              # 신규
+```
+
+(2) `_make_http()` 함수와 `DEFAULT_RATE_LIMIT_SEC` 상수는 제거 (또는 deprecate). 더 이상 사용 안 함.
+
+(3) `_process_one()` 함수를 다음으로 교체:
+```python
+async def _process_one(
+    ticker: str, name: str, articles: List[Dict[str, Any]],
+    sem: asyncio.Semaphore, llm, model: str,
+) -> Dict[str, Any]:
+    async with sem:
+        return await _analyzer.score_sentiment(
+            llm, ticker, articles, name=name, model=model,
+        )
+```
+
+(4) `refresh_daily()` 시그니처 + 본문 교체:
+```python
+async def refresh_daily(
+    conn: sqlite3.Connection,
+    asof: dt.date,
+    *,
+    top_n: int = DEFAULT_TOP_N,
+    concurrency: int = DEFAULT_CONCURRENCY,
+    max_news_per_ticker: int = DEFAULT_NEWS_PER_TICKER,
+    window_days: int = 1,
+    model: str = _analyzer.DEFAULT_MODEL,
+) -> Dict[str, Any]:
+    started = time.time()
+    tickers = _top_market_cap_tickers(conn, n=top_n)
+    name_map = {
+        r[0]: r[1] for r in conn.execute(
+            f"SELECT ticker, name FROM krx_master WHERE ticker IN "
+            f"({','.join('?' * len(tickers))})", tickers,
+        ).fetchall()
+    } if tickers else {}
+
+    articles_by_ticker, mapping_stats = articles_source.gather_articles_for_tickers(
+        conn, tickers, asof,
+        window_days=window_days,
+        max_per_ticker=max_news_per_ticker,
+    )
+
+    sem = asyncio.Semaphore(concurrency)
+    async with _make_llm() as llm:
+        tasks = []
+        for t in tickers:
+            arts = articles_by_ticker.get(t, [])
+            if not arts:
+                continue  # 매핑 0 — score 미생성
+            tasks.append(_process_one(t, name_map.get(t, t), arts, sem, llm, model))
+        raw_results = await asyncio.gather(*tasks, return_exceptions=True)
+
+    successes: List[Dict[str, Any]] = []
+    failures: List[str] = []
+    for r in raw_results:
+        if isinstance(r, BaseException):
+            failures.append(repr(r))
+        elif isinstance(r, dict):
+            successes.append(r)
+
+    if successes:
+        _upsert_news_sentiment(conn, asof, successes, source="articles")
+
+    top_pos = sorted(successes, key=lambda r: -r["score_raw"])[:5]
+    top_neg = sorted(successes, key=lambda r: r["score_raw"])[:5]
+
+    return {
+        "asof": asof.isoformat(),
+        "updated": len(successes),
+        "failures": failures,
+        "duration_sec": round(time.time() - started, 2),
+        "tokens_input": sum(r["tokens_input"] for r in successes),
+        "tokens_output": sum(r["tokens_output"] for r in successes),
+        "top_pos": top_pos,
+        "top_neg": top_neg,
+        "model": model,
+        "mapping": mapping_stats,
+    }
+```
+
+(5) `_upsert_news_sentiment()` 함수에 `source` 인자 추가 + INSERT 에 컬럼 포함:
+```python
+def _upsert_news_sentiment(
+    conn: sqlite3.Connection, asof: dt.date,
+    rows: List[Dict[str, Any]], *, source: str = "articles",
+) -> None:
+    iso = asof.isoformat()
+    data = [
+        (
+            r["ticker"], iso, r["score_raw"], r["reason"], r["news_count"],
+            r["tokens_input"], r["tokens_output"], r["model"], source,
+        )
+        for r in rows
+    ]
+    conn.executemany(
+        """INSERT INTO news_sentiment
+             (ticker, date, score_raw, reason, news_count,
+              tokens_input, tokens_output, model, source)
+           VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?)
+           ON CONFLICT(ticker, date) DO UPDATE SET
+             score_raw=excluded.score_raw,
+             reason=excluded.reason,
+             news_count=excluded.news_count,
+             tokens_input=excluded.tokens_input,
+             tokens_output=excluded.tokens_output,
+             model=excluded.model,
+             source=excluded.source
+        """,
+        data,
+    )
+    conn.commit()
+```
+
+- [ ] **Step 4: 테스트 통과 확인**
+
+```bash
+python -m pytest tests/test_ai_news_pipeline.py -v
+```
+Expected: PASS — `test_refresh_daily_happy_path`, `test_refresh_daily_failures_isolated`, `test_refresh_daily_no_match_ticker_skipped`, `test_top_market_cap_tickers` 모두 통과 (4 tests).
+
+- [ ] **Step 5: Commit**
+
+```bash
+git add app/screener/ai_news/pipeline.py tests/test_ai_news_pipeline.py
+git commit -m "feat(ai_news): pipeline uses articles_source (replaces Naver scraper)"
+```
+
+---
+
+### Task 5: `telegram.py` — 매핑 라인 추가
+
+**Files:**
+- Modify: `web-backend/stock-lab/app/screener/ai_news/telegram.py`
+- Modify: `web-backend/stock-lab/tests/test_ai_news_telegram.py`
+
+- [ ] **Step 1: 테스트 갱신 (실패 유도)**
+
+`tests/test_ai_news_telegram.py` 끝에 새 테스트 추가:
+```python
+def test_build_message_includes_mapping_line():
+    msg = tg.build_message(
+        asof="2026-05-14",
+        top_pos=[_row("005930", 8.5, "HBM 호재")],
+        top_neg=[],
+        tokens_input=1000, tokens_output=200,
+        mapping={"total_articles": 35, "matched_pairs": 50, "hit_tickers": 42},
+    )
+    assert "매핑" in msg
+    assert "42" in msg
+    assert "50" in msg
+    assert "35" in msg
+
+
+def test_build_message_without_mapping_omits_line():
+    msg = tg.build_message(
+        asof="2026-05-14",
+        top_pos=[],
+        top_neg=[],
+        tokens_input=1000, tokens_output=200,
+    )
+    assert "매핑" not in msg
+```
+
+- [ ] **Step 2: 테스트 실패 확인**
+
+```bash
+python -m pytest tests/test_ai_news_telegram.py -v
+```
+Expected: FAIL — `mapping` 인자 미지원.
+
+- [ ] **Step 3: `telegram.py` 의 `build_message` 시그니처 + footer 갱신**
+
+```python
+def build_message(
+    *,
+    asof: str,
+    top_pos: List[Dict[str, Any]],
+    top_neg: List[Dict[str, Any]],
+    tokens_input: int,
+    tokens_output: int,
+    mapping: Dict[str, int] | None = None,
+) -> str:
+    lines: List[str] = [
+        f"🌅 *AI 뉴스 분석* \\({_escape(asof)} 08:00\\)",
+        "",
+        "📈 *호재 Top 5*",
+    ]
+    if top_pos:
+        for i, r in enumerate(top_pos, 1):
+            lines.append(_row_line(i, r))
+    else:
+        lines.append(_escape("- (없음)"))
+
+    lines += ["", "📉 *악재 Top 5*"]
+    if top_neg:
+        for i, r in enumerate(top_neg, 1):
+            lines.append(_row_line(i, r))
+    else:
+        lines.append(_escape("- (없음)"))
+
+    cost = _cost_won(tokens_input, tokens_output)
+    mapping_part = ""
+    if mapping:
+        mapping_part = (
+            f"매핑 {mapping['hit_tickers']}/100 ticker "
+            f"\\({mapping['matched_pairs']}쌍 / articles {mapping['total_articles']}건\\) · "
+        )
+    lines += [
+        "",
+        f"_분석: 시총 상위 100종목 · {mapping_part}"
+        f"토큰 {tokens_input:,} in / {tokens_output:,} out · "
+        f"약 ₩{cost:,}_",
+    ]
+    return "\n".join(lines)
+```
+
+- [ ] **Step 4: 테스트 통과 확인**
+
+```bash
+python -m pytest tests/test_ai_news_telegram.py -v
+```
+Expected: PASS — 6 tests (기존 4 + 신규 2) 모두 통과.
+
+- [ ] **Step 5: Commit**
+
+```bash
+git add app/screener/ai_news/telegram.py tests/test_ai_news_telegram.py
+git commit -m "feat(ai_news): telegram includes article mapping stats line"
+```
+
+---
+
+### Task 6: `router.py` — mapping 응답 필드 전달
+
+**Files:**
+- Modify: `web-backend/stock-lab/app/screener/router.py`
+- Modify: `web-backend/stock-lab/tests/test_ai_news_router.py`
+
+- [ ] **Step 1: 테스트 갱신**
+
+`tests/test_ai_news_router.py` 의 `test_refresh_news_sentiment_weekday_invokes_pipeline` 보강:
+```python
+def test_refresh_news_sentiment_weekday_invokes_pipeline():
+    fake_summary = {
+        "asof": "2026-05-13", "updated": 3, "failures": [],
+        "duration_sec": 1.0, "tokens_input": 100, "tokens_output": 20,
+        "top_pos": [], "top_neg": [], "model": "m",
+        "mapping": {"total_articles": 5, "matched_pairs": 8, "hit_tickers": 3},
+    }
+    with patch("app.screener.router._ai_pipeline") as mp, \
+         patch("app.screener.router._ai_telegram") as mt:
+        mp.refresh_daily = AsyncMock(return_value=fake_summary)
+        mt.build_message = lambda **kw: f"TEXT_with_mapping={kw.get('mapping')}"
+        client = TestClient(app)
+        resp = client.post(
+            "/api/stock/screener/snapshot/refresh-news-sentiment?asof=2026-05-13"
+        )
+    assert resp.status_code == 200
+    body = resp.json()
+    assert body["mapping"]["hit_tickers"] == 3
+    assert "mapping=" in body["telegram_text"]
+```
+
+- [ ] **Step 2: 테스트 실패 확인**
+
+```bash
+python -m pytest tests/test_ai_news_router.py -v
+```
+Expected: FAIL — `mapping` 이 build_message 호출에 전달되지 않음.
+
+- [ ] **Step 3: `router.py` 의 `post_refresh_news_sentiment` 의 telegram_text 빌드 갱신**
+
+기존:
+```python
+    summary["telegram_text"] = _ai_telegram.build_message(
+        asof=summary["asof"],
+        top_pos=summary["top_pos"], top_neg=summary["top_neg"],
+        tokens_input=summary["tokens_input"],
+        tokens_output=summary["tokens_output"],
+    )
+```
+
+다음으로 교체:
+```python
+    summary["telegram_text"] = _ai_telegram.build_message(
+        asof=summary["asof"],
+        top_pos=summary["top_pos"], top_neg=summary["top_neg"],
+        tokens_input=summary["tokens_input"],
+        tokens_output=summary["tokens_output"],
+        mapping=summary.get("mapping"),
+    )
+```
+
+- [ ] **Step 4: 테스트 통과 확인**
+
+```bash
+python -m pytest tests/test_ai_news_router.py -v
+```
+Expected: PASS — 2 tests.
+
+- [ ] **Step 5: Commit**
+
+```bash
+git add app/screener/router.py tests/test_ai_news_router.py
+git commit -m "feat(ai_news): router forwards mapping stats to telegram"
+```
+
+---
+
+### Task 7: 전체 회귀 + scraper deprecate 주석
+
+**Files:**
+- Modify: `web-backend/stock-lab/app/screener/ai_news/scraper.py` (주석만)
+
+- [ ] **Step 1: scraper.py 상단에 deprecate 주석 추가**
+
+기존 docstring 을 다음으로 교체:
+```python
+"""[DEPRECATED] 네이버 finance 종목 뉴스 스크래핑.
+
+본 모듈은 ai_news Phase 1 (2026-05-14, `cdfa31b` spec) 에서 더 이상
+파이프라인에서 사용되지 않음. 데이터 소스는 stock-lab 의 articles 테이블
+(`ai_news/articles_source.py`) 로 전환됨.
+
+삭제 시점: Phase 2 (DART 도입) 결정 후. IC 검증 4주 누적 후 노드 활성화
+여부에 따라 본 모듈을 (a) 완전 삭제 또는 (b) DART 와 함께 ensemble
+fallback 으로 재활용.
+"""
+```
+
+다른 라인은 유지 (테스트가 여전히 import 함).
+
+- [ ] **Step 2: 전체 stock-lab 테스트 실행**
+
+```bash
+cd C:\Users\jaeoh\Desktop\workspace\web-backend\stock-lab
+python -m pytest --ignore=app/test_scraper.py -q
+```
+Expected: 신규 6 + 갱신 테스트 포함 **82 tests passed** (이전 76 + ai_news_articles_source 6 - 변동 없음).
+
+- [ ] **Step 3: Commit**
+
+```bash
+git add app/screener/ai_news/scraper.py
+git commit -m "docs(ai_news): mark scraper.py deprecated (Phase 1 transition)"
+```
+
+---
+
+### Task 8: 운영 검증 + 배포
+
+**Files:** (실행만, 수동 점검)
+
+- [ ] **Step 1: backend push**
+
+```bash
+cd C:\Users\jaeoh\Desktop\workspace\web-backend
+git push origin main
+```
+실패 시: 사용자에게 Gitea 자격증명 입력 요청.
+
+- [ ] **Step 2: deployer 반영 확인 (~1분)**
+
+```bash
+docker logs stock-lab --tail 20 2>&1 | grep -i "starting\|started"
+docker logs agent-office --tail 20 2>&1 | grep -i "starting\|started"
+```
+두 컨테이너 모두 새 startup 시각 확인.
+
+- [ ] **Step 3: 운영 DB 마이그레이션 자동 적용 확인**
+
+```bash
+docker exec stock-lab python -c "
+import sqlite3
+c = sqlite3.connect('/app/data/stock.db')
+cols = [r[1] for r in c.execute('PRAGMA table_info(news_sentiment)').fetchall()]
+print('news_sentiment columns:', cols)
+print('has source:', 'source' in cols)
+"
+```
+Expected: `has source: True`.
+
+- [ ] **Step 4: 수동 트리거**
+
+```bash
+curl -X POST "https://gahusb.synology.me/api/agent-office/command" \
+  -H "Content-Type: application/json" \
+  -d '{"agent":"stock","action":"run_ai_news"}'
+```
+응답 `{"ok": true}` 받으면 30-60초 후 텔레그램에 메시지 도착.
+
+- [ ] **Step 5: 텔레그램 메시지 검증**
+
+수신 메시지에 다음 패턴 모두 포함되는지 확인:
+- `🌅 AI 뉴스 분석 (YYYY-MM-DD 08:00)` 헤더
+- `📈 호재 Top 5` / `📉 악재 Top 5` 섹션
+- 종목명 + 티커 형태 (예: `삼성전자 (005930)`)
+- `매핑 N/100 ticker (M쌍 / articles K건)` 라인 (신규)
+- 토큰/비용 라인
+
+매핑 hit_tickers 가 합리적 범위 (예: 20~60) 인지 확인.
+
+- [ ] **Step 6: DB 검증**
+
+```bash
+docker exec stock-lab python -c "
+import sqlite3
+c = sqlite3.connect('/app/data/stock.db')
+rows = c.execute('SELECT COUNT(*), SUM(news_count), SUM(tokens_input) FROM news_sentiment WHERE date = date(\"now\") AND source = \"articles\"').fetchone()
+print('articles rows / total_news / tokens:', rows)
+# Naver 데이터와 비교
+naver = c.execute('SELECT COUNT(*) FROM news_sentiment WHERE source = \"articles\"').fetchone()
+print('all articles-source rows:', naver[0])
+"
+```
+Expected: `articles rows >= 10` (매핑 hit 종목 수), `source='articles'`.
+
+- [ ] **Step 7: 메모리 업데이트**
+
+`C:\Users\jaeoh\.claude\projects\C--Users-jaeoh-Desktop-workspace-web-ui\memory\project_stock_screener.md` 의 hotfix 이력에 본 슬라이스 commits 추가:
+- Phase 1 (`cdfa31b` spec + 본 plan 의 task commit SHA들)
+- 매핑 hit-rate 측정 결과 (예: "첫 실행 매핑 42/100, articles 35건, LLM cost ₩42")
+- 다음 단계: 4주 후 IC 측정 결과 보고 Phase 2 (DART) 또는 노드 삭제 결정
+
+---
+
+## 완료 후 검증 체크리스트
+
+본 plan 완료 시:
+- [ ] stock-lab `news_sentiment` 테이블에 `source` 컬럼 존재
+- [ ] 운영 트리거 시 source='articles' 행 생성, news_count > 0
+- [ ] 텔레그램 메시지에 매핑 N/100 라인 표시
+- [ ] 외부 HTTP 호출 (Naver) 0건
+- [ ] LLM cost 텔레그램 ₩ 라인이 이전(~₩60)보다 작거나 비슷 (~₩40-80)
+- [ ] 단위 테스트 신규 6 + 갱신 4 모두 통과, 기존 회귀 없음
+- [ ] `news_sentiment.source` 컬럼이 idempotent 하게 추가 (재기동 시 재추가 시도 없음)
+- [ ] legacy `scraper.py` 에 deprecate 주석 (코드 보존)
+
+## 후속 슬라이스 (이번 plan 완료 후)
+
+본 spec §15 명시:
+- **Phase 1.5** — 매핑 hit-rate < 30% 면 alias dict 추가
+- **Phase 2** — 4주 IC ≥ 0.05 시 DART OpenAPI 추가
+- **Phase X** — IC < 0.05 시 노드 deprecate