Web app: show a corpus-match trust badge (item 8)

webapp/app.py _match_badge reads the MCP search tools' own signals -- the
'RETRIEVAL CAUTION' weak-match note and the 'No results matched' message the
server already emits -- and renders a badge above the answer: "Grounded" on a
direct match, "Weak match" when CanLex may lack a provision on point, or "No
matching source found". The agentic loop previously flattened results to prose,
so a public user got no sense of how well the corpus actually matched their
question. Reuses an existing signal; no new dependency.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

webapp/app.py

@@ -364,6 +364,26 @@ def _summarize_call(name: str, args: dict) -> str:
     return f"Calling {name}"
 
 
+def _match_badge(tool_log: list[tuple[str, dict, str]]) -> str:
+    """A trust badge reflecting how well CanLex's corpus matched the question,
+    read from the search tools' own signals: the MCP server prepends a
+    'RETRIEVAL CAUTION' note on a weak semantic match and a 'No results matched'
+    message when nothing is found. Public users get no sense of this otherwise --
+    the agent flattens results to prose -- so surface it explicitly."""
+    searches = [out for name, _a, out in tool_log
+                if name == "canlex_search_legislation"]
+    if not searches:
+        return ""
+    if all("No results matched" in s for s in searches):
+        return ("> ⚠️ **No matching CanLex source found** — this question may be "
+                "outside the corpus; treat the answer with extra caution.\n\n")
+    if any("RETRIEVAL CAUTION" in s for s in searches):
+        return ("> ⚠️ **Weak match** — CanLex may not contain a provision "
+                "directly on point; verify the answer against primary sources.\n\n")
+    return ("> ✅ **Grounded** — based on CanLex sources that directly matched "
+            "the question.\n\n")
+
+
 def _format_sources(tool_log: list[tuple[str, dict, str]]) -> str:
     """Render every tool call's output as one Markdown document for display."""
     if not tool_log:
@@ -457,8 +477,9 @@ async def _agentic_answer(question: str):
                             f"{finish_reason!s}). If this is MAX_TOKENS, "
                             "raise MAX_OUTPUT_TOKENS in app.py.")
                     answer_buf += turn_text
-                    yield status_md(thinking=False), answer_buf, \
-                        _format_sources(tool_log)
+                    yield (status_md(thinking=False),
+                           _match_badge(tool_log) + answer_buf,
+                           _format_sources(tool_log))
                     return
 
                 # Tool turn. If the model emitted a commentary fragment before
@@ -507,7 +528,9 @@ async def _agentic_answer(question: str):
                            _format_sources(tool_log))
             answer_buf += turn_text or \
                 "_(no answer produced after the tool-call budget was exhausted)_"
-            yield status_md(thinking=False), answer_buf, _format_sources(tool_log)
+            yield (status_md(thinking=False),
+                   _match_badge(tool_log) + answer_buf,
+                   _format_sources(tool_log))
 
 
 # --- Gradio handler -----------------------------------------------------------