signals: restore the pre-port flag marker emoji

#903 inadvertently replaced the legacy FLAG_MARKER (U+1F6A9, '🚩') with
'[!]', which broke any downstream dashboard / alert that searches span
names for the flag emoji. Restores the original marker and updates the
#910 docs pass to match.

- crates/brightstaff/src/signals/analyzer.rs: FLAG_MARKER back to
  "\\u{1F6A9}" with a comment noting the backwards-compatibility
  reason so it doesn't drift again.
- docs/source/concepts/signals.rst and docs/source/guides/observability/
  tracing.rst: swap every '[!]' reference (subheading text, example
  span name, tip box, dashboard query hint) back to 🚩.

Verified: cargo test -p brightstaff --lib (162 passed, 1 ignored);
sphinx-build clean on both files; rendered HTML shows 🚩 in all
flag-marker references.

Made-with: Cursor

crates/brightstaff/src/signals/analyzer.rs

@@ -21,9 +21,10 @@ use super::schemas::{
 use super::text_processing::NormalizedMessage;
 
 /// Marker appended to the span operation name when concerning signals are
-/// detected. Kept in sync with the previous implementation for backward
+/// detected. The 🚩 emoji (U+1F6A9) matches the pre-port implementation so
-/// compatibility with downstream consumers.
+/// downstream consumers that search for flagged traces by span-name emoji
-pub const FLAG_MARKER: &str = "[!]";
+/// keep working.
+pub const FLAG_MARKER: &str = "\u{1F6A9}";
 
 /// ShareGPT-shaped row used as the canonical input to the analyzer's
 /// detectors. `from` is one of `"human"`, `"gpt"`, `"function_call"`,

docs/source/concepts/signals.rst

@@ -402,7 +402,8 @@ Visual Flag Marker
 
 When concerning signals are detected (disengagement present, stagnation
 count > 2, any execution failure / loop, or overall quality ``poor``/
-``severe``), the marker ``[!]`` is appended to the span's operation name.
+``severe``), the marker 🚩 (U+1F6A9) is appended to the span's operation
+name.
 This makes flagged sessions immediately visible in trace UIs without
 requiring attribute filtering.
 
@@ -420,7 +421,7 @@ Example queries against the layered keys::
     signals.execution.failure.count > 0
     signals.environment.exhaustion.count > 0
 
-For flagged sessions, search for ``[!]`` in span names.
+For flagged sessions, search for 🚩 in span names.
 
 .. image:: /_static/img/signals_trace.png
    :width: 100%
@@ -507,7 +508,7 @@ Example Span
 A concerning session, showing both layered attributes and a per-instance
 event::
 
-    # Span name: "POST /v1/chat/completions gpt-5.2 [!]"
+    # Span name: "POST /v1/chat/completions gpt-5.2 🚩"
 
     # Top-level
     signals.quality            = "severe"
@@ -619,7 +620,7 @@ Mitigation strategies:
    causes.
 
 .. tip::
-   The ``[!]`` marker in the span name provides instant visual feedback in
+   The 🚩 marker in the span name provides instant visual feedback in
    trace UIs, while the structured attributes (``signals.quality``,
    ``signals.interaction.disengagement.severity``, etc.) and per-instance
    span events enable powerful querying and drill-down in your observability

docs/source/guides/observability/tracing.rst

@@ -114,11 +114,11 @@ Signals act as early warning indicators embedded in your traces:
 
 **Visual Flag Markers**
 
-When concerning signals are detected (disengagement, execution failures / loops, stagnation > 2, or ``poor`` / ``severe`` quality), Plano automatically appends a ``[!]`` marker to the span's operation name. This makes problematic traces immediately visible in your tracing UI without requiring additional queries.
+When concerning signals are detected (disengagement, execution failures / loops, stagnation > 2, or ``poor`` / ``severe`` quality), Plano automatically appends a 🚩 marker to the span's operation name. This makes problematic traces immediately visible in your tracing UI without requiring additional queries.
 
 **Example Span with Signals**::
 
-    # Span name: "POST /v1/chat/completions gpt-4 [!]"
+    # Span name: "POST /v1/chat/completions gpt-4 🚩"
     # Standard LLM attributes:
     llm.model = "gpt-4"
     llm.usage.total_tokens = 225