본문으로 건너뛰기
cccskills
무료GitHub에 공개

excel-creation-fallback

Recover from failed Excel creation or editing by switching from execute_code_sandbox to shell_agent. It guides clear task descriptions so the agent can install missing libraries, run code, retry errors, and confirm file creation.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

원문원문 설명 보기

Use shell_agent as fallback when execute_code_sandbox fails for Excel file operations

연동 도구Excel
설치 방법 보기

이럴 때 유용합니다

  • Continuing Excel creation after a sandbox import error
  • Creating a sales report with formulas and sample data
  • Building multiple sheets with conditional formatting
  • Preparing a tiered pricing table with a financial summary

포함된 파일(2)

  • SKILL.md3.6 KB
  • .skill_id37 B

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

Excel File Creation Fallback

When execute_code_sandbox fails for openpyxl or Excel operations, delegate to shell_agent which can autonomously handle dependency and environment issues.

When to Use

  • execute_code_sandbox fails with import errors for openpyxl or related libraries
  • The sandbox environment lacks required dependencies
  • You need to create or modify Excel files with complex requirements
  • Repeated sandbox execution failures for file I/O operations

Steps

Step 1: Attempt with execute_code_sandbox first

Try creating the Excel file using Python's openpyxl library in the code sandbox:

from openpyxl import Workbook

wb = Workbook()
ws = wb.active
ws.append(['Column1', 'Column2', 'Column3'])
wb.save('output.xlsx')

Step 2: If it fails, switch to shell_agent

Delegate the task to shell_agent with a clear, comprehensive task description:

Create an Excel file named 'output.xlsx' with the following structure:
- Sheet 1: Data with columns [Date, Metric, Value]
- Include sample data rows with realistic values
- Apply basic formatting (bold headers, cell borders)
- Add a summary section with totals or averages
- Save the file in the current directory

Step 3: Let shell_agent handle the environment

The shell_agent will:

  • Decide whether to use Python or Bash
  • Install dependencies if needed (e.g., pip install openpyxl)
  • Write and execute the code
  • Automatically retry and fix errors (up to several rounds)
  • Confirm the file was created successfully

Example Task Descriptions

Basic Excel file:

Create an Excel file named 'sales_report.xlsx' with headers: Date, Product, Quantity, Price, Total. Add 10 sample rows of data and a formula column for Total (Quantity * Price).

Complex Excel with formatting:

Create an Excel file with multiple sheets:
- Sheet 'Summary': Key metrics and totals
- Sheet 'Details': Full transaction data with columns [ID, Date, Customer, Amount, Status]
- Apply conditional formatting to highlight amounts over 1000
- Add borders to all cells and bold headers

Tiered pricing structure:

Create an Excel file with a tiered pricing table:
- Column A: Quantity thresholds (0, 100, 500, 1000)
- Column B: Unit price at each tier
- Column C: Discount percentage (e.g., 15% discount over 1000 units)
- Include a financial summary section with projections

Why This Pattern Works

shell_agent has several advantages over execute_code_sandbox for file creation tasks:

Featureexecute_code_sandboxshell_agent
Dependency installationManual/preset onlyAutonomous
Error recoveryReturns errorAuto-retries and fixes
Tool selectionPython onlyPython, Bash, or other
Filesystem accessSandbox-limitedFull workspace access
VerificationNoneCan verify file creation

Troubleshooting

If shell_agent also struggles:

  1. Be more specific - Include exact column names, data types, and formatting requirements
  2. Provide sample data - Include example rows to clarify expected output
  3. Break it down - For complex files, request creation in stages
  4. Check permissions - Ensure the target directory is writable

Alternative Approaches

If shell_agent is unavailable or unsuitable:

  • Use run_shell with explicit commands (if you know the exact syntax)
  • Check for alternative libraries (xlsxwriter, pandas with openpyxl engine)
  • Use CSV as intermediate format, then convert to Excel

리뷰

아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.

댓글

로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.

아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.

보내면 바로 공개됩니다. 이메일 주소나 전화번호 같은 개인 정보는 쓰지 마세요. URL은 2개까지입니다.

0 / 1,000자

이 양식은 reCAPTCHA로 보호되며 Google 개인정보처리방침 및 서비스 약관이 적용됩니다.

같은 저장소의 스킬

Prepare audio stems, the separate parts of a track, for mixing by matching their durations with silence, loops, or crossfades. Verify each generated and processed file before moving to the next production step.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Match audio parts with different durations
  • Extend drums and melodic parts using suitable methods
  • Check audio specifications before mixing
HKUDS/OpenSpace7.8천2026년 8월 13일 업데이트

Produce audio in separate stems, meaning individual instrument tracks, and verify each output as you go. Align track lengths with silence, loops, or crossfades, then apply effects, mix a master, and package the files.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Align instrument tracks to a reference audio file
  • Choose how to extend tracks that are too short
  • Verify audio properties after generation and effects
HKUDS/OpenSpace7.8천2026년 8월 13일 업데이트

Build serverless endpoints that relay external API requests for a dashboard while keeping API keys on the server. Includes Vercel examples for input checks, caching, cross-origin access, and consistent JSON responses.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Connect a dashboard to external APIs without exposing API keys
  • Create endpoints for stock quotes and news
  • Standardize API responses and error handling
HKUDS/OpenSpace7.8천2026년 8월 13일 업데이트

Produce a master track and separate audio parts through a structured Python workflow. Apply filters and reverb, export WAV files with consistent settings, package them in a ZIP archive, and check that the deliverables meet the requested specifications.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Export a master track with separate audio parts
  • Apply filters and reverb to audio
  • Check duration and format across deliverables
HKUDS/OpenSpace7.8천2026년 8월 13일 업데이트

Keep document creation moving when web searches and page retrieval repeatedly fail. The skill preserves the original task, uses the model’s existing knowledge, and clearly identifies information that could not be checked against external sources.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Continue drafting after repeated web retrieval failures
  • Preserve task requirements during network errors
  • Mark information that could not be externally verified
HKUDS/OpenSpace7.8천2026년 8월 13일 업데이트

When Python execution repeatedly fails in execute_code_sandbox, use a file-based alternative: save the script, run it through the shell, and capture results or errors. The guidance covers paths, imports, timeouts, structured output, and optional cleanup.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Retry Python work through the shell after repeated sandbox failures
  • Run longer tasks with an adjusted timeout
  • Execute Python work that needs multiple files or system utilities
HKUDS/OpenSpace7.8천2026년 8월 13일 업데이트

HKUDS의 스킬 모두 보기

이 스킬의 문제 신고