feat(B2): add Microsoft Word (.docx) support

Implements ROADMAP task B2 — full .docx scraping support via mammoth +
python-docx, producing SKILL.md + references/ output identical to other
source types.

New files:
- src/skill_seekers/cli/word_scraper.py — WordToSkillConverter class +
  main() entry point (~600 lines); mammoth → BeautifulSoup pipeline;
  handles headings, code detection (incl. monospace <p><br> blocks),
  tables, images, metadata extraction
- src/skill_seekers/cli/arguments/word.py — add_word_arguments() +
  WORD_ARGUMENTS dict
- src/skill_seekers/cli/parsers/word_parser.py — WordParser for unified
  CLI parser registry
- tests/test_word_scraper.py — comprehensive test suite (~300 lines)

Modified files:
- src/skill_seekers/cli/main.py — registered "word" command module
- src/skill_seekers/cli/source_detector.py — .docx auto-detection +
  _detect_word() classmethod
- src/skill_seekers/cli/create_command.py — _route_word() + --help-word
- src/skill_seekers/cli/arguments/create.py — WORD_ARGUMENTS + routing
- src/skill_seekers/cli/arguments/__init__.py — export word args
- src/skill_seekers/cli/parsers/__init__.py — register WordParser
- src/skill_seekers/cli/unified_scraper.py — _scrape_word() integration
- src/skill_seekers/cli/pdf_scraper.py — fix: real enhancement instead
  of stub; remove [:3] reference file limit; capture run_workflows return
- src/skill_seekers/cli/github_scraper.py — fix: remove arbitrary
  open_issues[:20] / closed_issues[:10] reference file limits
- pyproject.toml — skill-seekers-word entry point + docx optional dep
- tests/test_cli_parsers.py — update parser count 21→22

Bug fixes applied during real-world testing:
- Code detection: detect monospace <p><br> blocks as code (mammoth
  renders Courier paragraphs this way, not as <pre>/<code>)
- Language detector: fix wrong method name detect_from_text →
  detect_from_code
- Description inference: pass None from main() so extract_docx() can
  infer description from Word document subject/title metadata
- Bullet-point guard: exclude prose starting with •/-/* from code scoring
- Enhancement: implement real API/LOCAL enhancement (was stub)
- pip install message: add quotes around skill-seekers[docx]

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

src/skill_seekers/cli/unified_scraper.py

@@ -73,11 +73,12 @@ class UnifiedScraper:
             "documentation": [],  # List of doc sources
             "github": [],  # List of github sources
             "pdf": [],  # List of pdf sources
+            "word": [],  # List of word sources
             "local": [],  # List of local sources (docs or code)
         }
 
         # Track source index for unique naming (multi-source support)
-        self._source_counters = {"documentation": 0, "github": 0, "pdf": 0, "local": 0}
+        self._source_counters = {"documentation": 0, "github": 0, "pdf": 0, "word": 0, "local": 0}
 
         # Output paths - cleaner organization
         self.name = self.config["name"]
@@ -151,6 +152,8 @@ class UnifiedScraper:
                     self._scrape_github(source)
                 elif source_type == "pdf":
                     self._scrape_pdf(source)
+                elif source_type == "word":
+                    self._scrape_word(source)
                 elif source_type == "local":
                     self._scrape_local(source)
                 else:
@@ -514,6 +517,65 @@ class UnifiedScraper:
 
         logger.info(f"✅ PDF: {len(pdf_data.get('pages', []))} pages extracted")
 
+    def _scrape_word(self, source: dict[str, Any]):
+        """Scrape Word document (.docx)."""
+        try:
+            from skill_seekers.cli.word_scraper import WordToSkillConverter
+        except ImportError:
+            logger.error("word_scraper.py not found")
+            return
+
+        # Multi-source support: Get unique index for this Word source
+        idx = self._source_counters["word"]
+        self._source_counters["word"] += 1
+
+        # Extract Word identifier for unique naming (filename without extension)
+        docx_path = source["path"]
+        docx_id = os.path.splitext(os.path.basename(docx_path))[0]
+
+        # Create config for Word scraper
+        word_config = {
+            "name": f"{self.name}_word_{idx}_{docx_id}",
+            "docx_path": source["path"],
+            "description": f"{source.get('name', docx_id)} documentation",
+        }
+
+        # Scrape
+        logger.info(f"Scraping Word document: {source['path']}")
+        converter = WordToSkillConverter(word_config)
+
+        # Extract Word content
+        converter.extract_docx()
+
+        # Load extracted data from file
+        word_data_file = converter.data_file
+        with open(word_data_file, encoding="utf-8") as f:
+            word_data = json.load(f)
+
+        # Copy data file to cache
+        cache_word_data = os.path.join(self.data_dir, f"word_data_{idx}_{docx_id}.json")
+        shutil.copy(word_data_file, cache_word_data)
+
+        # Append to list
+        self.scraped_data["word"].append(
+            {
+                "docx_path": docx_path,
+                "docx_id": docx_id,
+                "idx": idx,
+                "data": word_data,
+                "data_file": cache_word_data,
+            }
+        )
+
+        # Build standalone SKILL.md for synthesis
+        try:
+            converter.build_skill()
+            logger.info("✅ Word: Standalone SKILL.md created")
+        except Exception as e:
+            logger.warning(f"⚠️  Failed to build standalone Word SKILL.md: {e}")
+
+        logger.info(f"✅ Word: {len(word_data.get('pages', []))} sections extracted")
+
     def _scrape_local(self, source: dict[str, Any]):
         """
         Scrape local directory (documentation files or source code).