feat: Add WebSearch as third source with zero-config fallback

Add Claude's built-in WebSearch tool as a third research source for
/last30days. This enables the skill to work out of the box with zero
API keys while preserving Reddit/X as the primary sources.

Key changes:
- Add WebSearchItem schema for web results (no engagement metrics)
- Add score_websearch_items() with 55/45 relevance/recency weighting
- Apply -15pt source penalty so WebSearch ranks below Reddit/X
- Add --include-web CLI flag to opt-in to WebSearch
- Return 'web' mode when no API keys configured (zero-config)
- Update render.py with [WEB] source label formatting

When WebSearch is enabled, the script outputs instructions for Claude
to use its built-in WebSearch tool, then synthesize results together.

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

scripts/lib/schema.py

@@ -138,6 +138,37 @@ class XItem:
         }
 
 
+@dataclass
+class WebSearchItem:
+    """Normalized web search item (no engagement metrics)."""
+    id: str
+    title: str
+    url: str
+    source_domain: str  # e.g., "medium.com", "github.com"
+    snippet: str
+    date: Optional[str] = None
+    date_confidence: str = "low"
+    relevance: float = 0.5
+    why_relevant: str = ""
+    subs: SubScores = field(default_factory=SubScores)
+    score: int = 0
+
+    def to_dict(self) -> Dict[str, Any]:
+        return {
+            'id': self.id,
+            'title': self.title,
+            'url': self.url,
+            'source_domain': self.source_domain,
+            'snippet': self.snippet,
+            'date': self.date,
+            'date_confidence': self.date_confidence,
+            'relevance': self.relevance,
+            'why_relevant': self.why_relevant,
+            'subs': self.subs.to_dict(),
+            'score': self.score,
+        }
+
+
 @dataclass
 class Report:
     """Full research report."""
@@ -145,17 +176,19 @@ class Report:
     range_from: str
     range_to: str
     generated_at: str
-    mode: str  # 'reddit-only', 'x-only', 'both'
+    mode: str  # 'reddit-only', 'x-only', 'both', 'web-only', etc.
     openai_model_used: Optional[str] = None
     xai_model_used: Optional[str] = None
     reddit: List[RedditItem] = field(default_factory=list)
     x: List[XItem] = field(default_factory=list)
+    web: List[WebSearchItem] = field(default_factory=list)
     best_practices: List[str] = field(default_factory=list)
     prompt_pack: List[str] = field(default_factory=list)
     context_snippet_md: str = ""
     # Status tracking
     reddit_error: Optional[str] = None
     x_error: Optional[str] = None
+    web_error: Optional[str] = None
     # Cache info
     from_cache: bool = False
     cache_age_hours: Optional[float] = None
@@ -173,6 +206,7 @@ class Report:
             'xai_model_used': self.xai_model_used,
             'reddit': [r.to_dict() for r in self.reddit],
             'x': [x.to_dict() for x in self.x],
+            'web': [w.to_dict() for w in self.web],
             'best_practices': self.best_practices,
             'prompt_pack': self.prompt_pack,
             'context_snippet_md': self.context_snippet_md,
@@ -181,6 +215,8 @@ class Report:
             d['reddit_error'] = self.reddit_error
         if self.x_error:
             d['x_error'] = self.x_error
+        if self.web_error:
+            d['web_error'] = self.web_error
         if self.from_cache:
             d['from_cache'] = self.from_cache
         if self.cache_age_hours is not None:
@@ -240,6 +276,24 @@ class Report:
                 score=x.get('score', 0),
             ))
 
+        # Reconstruct Web items
+        web_items = []
+        for w in data.get('web', []):
+            subs = SubScores(**w.get('subs', {})) if w.get('subs') else SubScores()
+            web_items.append(WebSearchItem(
+                id=w['id'],
+                title=w['title'],
+                url=w['url'],
+                source_domain=w.get('source_domain', ''),
+                snippet=w.get('snippet', ''),
+                date=w.get('date'),
+                date_confidence=w.get('date_confidence', 'low'),
+                relevance=w.get('relevance', 0.5),
+                why_relevant=w.get('why_relevant', ''),
+                subs=subs,
+                score=w.get('score', 0),
+            ))
+
         return cls(
             topic=data['topic'],
             range_from=range_from,
@@ -250,11 +304,13 @@ class Report:
             xai_model_used=data.get('xai_model_used'),
             reddit=reddit_items,
             x=x_items,
+            web=web_items,
             best_practices=data.get('best_practices', []),
             prompt_pack=data.get('prompt_pack', []),
             context_snippet_md=data.get('context_snippet_md', ''),
             reddit_error=data.get('reddit_error'),
             x_error=data.get('x_error'),
+            web_error=data.get('web_error'),
             from_cache=data.get('from_cache', False),
             cache_age_hours=data.get('cache_age_hours'),
         )