@@ -133,7 +133,7 @@ def set_skills_metadata(self, metadata: list[dict[str, Any]]) -> None:
133133 self ._skills_metadata = metadata
134134
135135 def _is_local_eval_sandbox (self ) -> bool :
136- """Check if the sandbox is a local- eval type (has in-memory namespaces).
136+ """Check if the sandbox is a eval type (has in-memory namespaces).
137137
138138 This checks the actual sandbox instance, not the config, to handle
139139 cases where an external sandbox is passed that differs from config.
@@ -202,7 +202,7 @@ async def _setup_sandbox_environment(self) -> None:
202202 # Use /tmp so 'from generated.mcp...' works (files are at /tmp/generated/)
203203 sandbox_generated_path = "/tmp"
204204 else :
205- # For local- eval, use the parent directory so 'from generated.mcp...' works
205+ # For eval, use the parent directory so 'from generated.mcp...' works
206206 # The generated_path might be './generated', we need its parent on sys.path
207207 sandbox_generated_path = str (generated_path .parent )
208208
@@ -705,7 +705,7 @@ def generate_skills_in_sandbox(self) -> None:
705705 skill scripts **directly** in the Jupyter kernel, reading the script
706706 files from the shared ``skills_path`` on disk. This avoids the
707707 HTTP proxy round-trip (call_tool → MCP proxy → agent-runtimes →
708- local- eval fallback) which caused blocking and deadlocks.
708+ eval fallback) which caused blocking and deadlocks.
709709
710710 The skills_path is the same between the agent-runtimes process and
711711 the Jupyter runtime (shared filesystem or mount).
@@ -717,7 +717,7 @@ def generate_skills_in_sandbox(self) -> None:
717717 if self ._sandbox is None or not self ._skills_metadata :
718718 return
719719
720- # Skip for local- eval sandboxes (they use the on-disk generated files)
720+ # Skip for eval sandboxes (they use the on-disk generated files)
721721 if self ._is_local_eval_sandbox ():
722722 return
723723
@@ -1032,7 +1032,7 @@ async def execute(
10321032
10331033 # Get the generated path for sys.path setup
10341034 # For remote sandboxes, use /tmp so 'from generated.mcp...' works (files at /tmp/generated/)
1035- # For local- eval, use parent of generated_path so 'from generated.mcp...' works
1035+ # For eval, use parent of generated_path so 'from generated.mcp...' works
10361036 # Use actual sandbox type detection, not config
10371037 is_local_eval = self ._is_local_eval_sandbox ()
10381038 if not is_local_eval :
@@ -1086,7 +1086,7 @@ async def execute(
10861086'''
10871087 # Branch based on actual sandbox type (already computed above)
10881088 if is_local_eval :
1089- # For local- eval, we can access _namespaces directly
1089+ # For eval, we can access _namespaces directly
10901090 return await self ._execute_local_eval (code , setup_code , timeout )
10911091 else :
10921092 # For Jupyter/remote sandboxes, use run_code()
@@ -1099,7 +1099,7 @@ async def _execute_local_eval(
10991099 setup_code : str ,
11001100 timeout : Optional [float ] = None ,
11011101 ) -> ExecutionResult :
1102- """Execute code in local- eval sandbox with direct namespace access."""
1102+ """Execute code in eval sandbox with direct namespace access."""
11031103 import sys
11041104 import io
11051105 import time
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