feat: local content-mining platform for YouTube creator scraping

Scraper de canales de YouTube hacia notas Markdown para base de conocimiento
(Obsidian-ready), con plataforma web local.

Engine + CLI (Workstream A):
- Modular pipeline: discover/extract/parse/chapters/render/store + ratelimit
- SQLite store con migración idempotente: FTS5 (transcript search), columnas
  de metadata enriquecida, tablas cookies_meta y scrape_jobs
- Módulos: segments, cookies (Netscape vault), export (json/csv/srt/html),
  analysis (word freq/timeline/wordcloud), monitor (watch loop), pipeline
- CLI Click group: search, export, audio, channels, watch, analyze, re-render
- Fix del bug de scoping de cookies en cli.py

Webapp local (Workstream B):
- FastAPI backend: dashboard, channels, videos facetado, transcript, search
  FTS, analysis, scrape jobs con SSE, cookies drag-and-drop, exports,
  folders (abrir en OS), tools (re-render, formato)
- SPA no-build (Alpine.js + Tailwind + Chart.js por CDN): 9 vistas, tema
  dark command-center con acento rojo→rosa, cookie vault drag-drop,
  consola de scrapeo con progreso live vía SSE

Launcher + subagentes (Workstream C):
- start-server.bat / stop-server.bat con auto port-scan + browser open
- .opencode/agent/webapp-builder.md + .opencode/goals/webapp-build.md

Tests: 38 pytest verdes. Sin funcionalidad de IA (enfoque data-mining).

tests/test_render.py

@@ -0,0 +1,77 @@
+from __future__ import annotations
+
+from pathlib import Path
+
+from yt_scraper.render import build_filename_stem, format_timestamp, quote_yaml
+from yt_scraper.chapters import Section
+from yt_scraper.parse import Segment
+
+TEMPLATES = Path(__file__).parent.parent / "templates"
+
+
+def test_format_timestamp_minutes():
+    assert format_timestamp(0.0) == "00:00"
+    assert format_timestamp(65.0) == "01:05"
+    assert format_timestamp(3599.0) == "59:59"
+
+
+def test_format_timestamp_hours():
+    assert format_timestamp(3661.0) == "01:01:01"
+
+
+def test_quote_yaml_plain():
+    assert quote_yaml("hola") == "hola"
+
+
+def test_quote_yaml_special():
+    result = quote_yaml('hello "world"')
+    assert result.startswith('"')
+    assert result.endswith('"')
+    assert '\\"' in result
+
+
+def test_quote_yaml_none():
+    assert quote_yaml(None) == '""'
+
+
+def test_build_filename_stem():
+    stem = build_filename_stem("20240115", "Mi Video Genial!")
+    assert stem.startswith("20240115")
+    assert "mi-video-genial" in stem.lower()
+
+
+def test_build_filename_stem_no_date():
+    stem = build_filename_stem(None, "Titulo")
+    assert "unknown" in stem
+    assert "titulo" in stem.lower()
+
+
+def test_render_markdown(tmp_path):
+    template_file = tmp_path / "test.j2"
+    template_file.write_text(
+        "---\ntitle: {{ title | quote_yaml }}\n---\n# {{ title }}\n\n"
+        "{% for s in sections %}## {{ s.title }}\n{% for seg in s.segments %}**{{ seg.start | format_timestamp }}** {{ seg.text }}\n{% endfor %}{% endfor %}",
+        encoding="utf-8",
+    )
+    out_dir = tmp_path / "out"
+    sections = [
+        Section(
+            title="Intro",
+            start=0.0,
+            segments=[Segment(start=0.0, end=1.0, text="Hola"), Segment(start=5.0, end=6.0, text="Mundo")],
+        )
+    ]
+    from yt_scraper.render import render_markdown
+
+    md_path = render_markdown(
+        template_file,
+        out_dir,
+        "20240115_test",
+        {"title": "Test Video", "sections": sections},
+    )
+    assert md_path.exists()
+    content = md_path.read_text(encoding="utf-8")
+    assert "# Test Video" in content
+    assert "## Intro" in content
+    assert "**00:00** Hola" in content
+    assert "**00:05** Mundo" in content