chore: apply pre-commit auto-fixes (trim trailing whitespace, EOF)

alfred/agent/agent.py

@@ -192,9 +192,7 @@ class Agent:
         if cache_key_value is not None:
             cached = memory.stm.tool_results.get(tool_name, cache_key_value)
             if cached is not None:
-                logger.info(
-                    f"Tool cache HIT: {tool_name}[{cache_key_value}]"
-                )
+                logger.info(f"Tool cache HIT: {tool_name}[{cache_key_value}]")
                 self._post_tool_side_effects(tool_name, args, cached, from_cache=True)
                 return {**cached, "_from_cache": True}
 

alfred/agent/prompt.py

@@ -165,7 +165,9 @@ EXPRESSIONS À UTILISER (une par situation, naturellement intégrées dans ta r
             lines.append("  Steps:")
             for step in steps:
                 step_id = step.get("id", "?")
-                step_tool = step.get("tool") or ("ask_user" if step.get("ask_user") else "—")
+                step_tool = step.get("tool") or (
+                    "ask_user" if step.get("ask_user") else "—"
+                )
                 lines.append(f"    - {step_id} ({step_tool})")
         lines.append("  Call end_workflow(reason) when done, cancelled, or off-topic.")
         return "\n".join(lines)

alfred/agent/tools/spec.py

@@ -27,9 +27,9 @@ class ToolSpecError(ValueError):
 class ParameterSpec:
     """Semantic description of a single tool parameter."""
 
-    description: str           # Short: what the value represents.
-    why_needed: str            # Why the tool needs this — drives LLM reasoning.
-    example: str | None = None # Concrete example value, shown to the LLM.
+    description: str  # Short: what the value represents.
+    why_needed: str  # Why the tool needs this — drives LLM reasoning.
+    example: str | None = None  # Concrete example value, shown to the LLM.
 
     @classmethod
     def from_dict(cls, name: str, data: dict) -> ParameterSpec:
@@ -38,7 +38,9 @@ class ParameterSpec:
         return cls(
             description=str(data["description"]).strip(),
             why_needed=str(data["why_needed"]).strip(),
-            example=str(data["example"]).strip() if data.get("example") is not None else None,
+            example=str(data["example"]).strip()
+            if data.get("example") is not None
+            else None,
         )
 
 
@@ -54,7 +56,9 @@ class ReturnsSpec:
         _require(data, "description", f"returns.{key}")
         fields = data.get("fields") or {}
         if not isinstance(fields, dict):
-            raise ToolSpecError(f"returns.{key}.fields must be a dict, got {type(fields).__name__}")
+            raise ToolSpecError(
+                f"returns.{key}.fields must be a dict, got {type(fields).__name__}"
+            )
         return cls(
             description=str(data["description"]).strip(),
             fields={str(k): str(v).strip() for k, v in fields.items()},
@@ -78,14 +82,14 @@ class ToolSpec:
     """Full semantic spec for one tool."""
 
     name: str
-    summary: str                              # One-liner — becomes Tool.description.
-    description: str                          # Longer paragraph.
+    summary: str  # One-liner — becomes Tool.description.
+    description: str  # Longer paragraph.
     when_to_use: str
     when_not_to_use: str | None
     next_steps: str | None
-    parameters: dict[str, ParameterSpec]      # name -> ParameterSpec
-    returns: dict[str, ReturnsSpec]           # status_key -> ReturnsSpec
-    cache: CacheSpec | None = None            # If present, tool is cached.
+    parameters: dict[str, ParameterSpec]  # name -> ParameterSpec
+    returns: dict[str, ReturnsSpec]  # status_key -> ReturnsSpec
+    cache: CacheSpec | None = None  # If present, tool is cached.
 
     @classmethod
     def from_yaml_path(cls, path: Path) -> ToolSpec:
@@ -200,6 +204,7 @@ class ToolSpec:
 # Helpers
 # ---------------------------------------------------------------------------
 
+
 def _require(data: dict, key: str, where: str) -> None:
     if data.get(key) is None or (isinstance(data[key], str) and not data[key].strip()):
         raise ToolSpecError(f"{where}: missing required field '{key}'")