Incremental audio production with duration mismatch handling, adaptive stem extension, and pre-mix alignment verification
日本語の概要は準備中です。原文の説明を表示しています。
Four-step recovery workflow for code execution failures when inline Python fails
インストール方法を見るインストールする前に、エージェントに与えられる指示の中身を確認できます。
This skill provides a systematic debugging approach when inline Python code execution fails, particularly in heredoc or shell_agent contexts.
When Python code execution fails, follow this recovery workflow:
.py fileApply this pattern when:
Try executing Python code inline first (using execute_code_sandbox or similar):
# Example: Attempt inline execution
import pandas as pd
import openpyxl
df = pd.read_excel("input.xlsx")
# Process data...
df.to_excel("output.xlsx", index=False)
If this succeeds, proceed. If it fails, move to Step 2.
When inline execution fails, write the complete script to a persistent file:
# Capture the script content
script_content = '''
import pandas as pd
import openpyxl
import sys
try:
# Your original code here
df = pd.read_excel("input.xlsx")
# Processing logic
result_df = df.groupby("category").sum()
# Output
result_df.to_excel("output.xlsx", index=False)
print("SUCCESS: File generated")
except Exception as e:
print(f"ERROR: {e}", file=sys.stderr)
sys.exit(1)
'''
# Write to file
with open("script.py", "w") as f:
f.write(script_content)
print("Script written to script.py")
Run the saved script using shell execution:
python script.py
Or with error capture:
python script.py 2>&1 | tee execution.log
This approach:
Verify the results are correct:
# Validation script
import pandas as pd
import os
# Check file exists
if os.path.exists("output.xlsx"):
df = pd.read_excel("output.xlsx")
print(f"Rows: {len(df)}, Columns: {len(df.columns)}")
print(df.head())
print("VALIDATION: PASSED")
else:
print("VALIDATION: FAILED - Output file missing")
# Full fallback workflow example
def generate_spreadsheet_fallback(data, output_path):
"""Generate spreadsheet with fallback workflow"""
# Step 1: Try inline
inline_script = f'''
import pandas as pd
data = {data}
df = pd.DataFrame(data)
df.to_excel("{output_path}", index=False)
'''
try:
# Attempt inline execution
result = execute_code_sandbox(code=inline_script)
if "error" not in result.lower():
return "SUCCESS_INLINE"
except Exception as e:
pass
# Step 2: Write to file
file_script = f'''
import pandas as pd
import sys
try:
data = {data}
df = pd.DataFrame(data)
df.to_excel("{output_path}", index=False)
print("SUCCESS")
except Exception as e:
print(f"ERROR: {{e}}", file=sys.stderr)
sys.exit(1)
'''
with open("generate.py", "w") as f:
f.write(file_script)
# Step 3: Execute file
shell_result = run_shell(command="python generate.py")
# Step 4: Validate
if os.path.exists(output_path):
return "SUCCESS_FILE"
else:
return "FAILED"
This pattern helps resolve:
retry-with-modification for iterative debuggingoutput-validation-check for result verificationerror-log-analysis for root cause identificationまだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Incremental audio production with duration mismatch handling, adaptive stem extension, and pre-mix alignment verification
日本語の概要は準備中です。原文の説明を表示しています。
Incremental audio production with duration alignment handling, per-stem verification, and adaptive extension strategies
日本語の概要は準備中です。原文の説明を表示しています。
Create serverless API proxy endpoints that hide API keys and provide a unified backend for the dashboard frontend. Designed for Vercel deployment.
日本語の概要は準備中です。原文の説明を表示しています。
End-to-end audio production workflow with stems, effects, archiving, and verification
日本語の概要は準備中です。原文の説明を表示しています。
Handle cascading data retrieval tool failures by falling back to embedded knowledge generation
日本語の概要は準備中です。原文の説明を表示しています。
Fallback pattern for executing Python code when execute_code_sandbox fails
日本語の概要は準備中です。原文の説明を表示しています。