본문으로 건너뛰기
cccskills
무료GitHub에 공개

sn-image-doctor

Check the SenseNova-Skills installation, Python dependencies, and environment variables before using other skills. Prompt for missing configuration, save supplied values to a .env file, and reload settings or suggest restarting the agent.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

원문원문 설명 보기

Environment diagnostic skill for SenseNova-Skills project. Checks that sn-image-base is properly installed and configured, validates dependencies and environment variables. Prompts user to configure missing required variables and saves them to .env file. After configuration, reloads environment and suggests agent restart if needed.

실행 점수 미검증

설치 방법 보기

이럴 때 유용합니다

  • Checking setup before using SenseNova-Skills
  • Finding missing Python dependencies
  • Entering and saving missing API configuration
  • Reloading settings after configuration changes

포함된 파일(2)

  • SKILL.md5.5 KB
  • scripts/check_environment.py6.2 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

sn-image-doctor

Overview

sn-image-doctor is an infrastructure skill (tier 0) that validates the SenseNova-Skills environment before running other skills. It ensures SenseNova-Skills project is properly installed and configured.

This skill performs comprehensive checks including:

  • Installation verification of SenseNova-Skills project
  • Python dependency validation
  • Environment variable configuration checks, with interactive prompts to configure missing required variables and save them to .env
  • Automatic environment reload after configuration changes, with agent restart suggestion if reload fails

Usage

Run the doctor check to validate your environment:

# Basic check
python scripts/check_environment.py

# Verbose output with detailed diagnostics
python scripts/check_environment.py --verbose

Output Format

Text Output

=== SenseNova-Skills Environment Check ===

[1/3] Checking sn-image-base installation...
  ✅ Installation looks good

[2/3] Checking Python dependencies...
  ✅ Python 3.11.0
  ✅ All required packages installed

[3/3] Checking environment variables...
  ❌ SN_IMAGE_GEN_API_KEY: Image generation API key is not set; configure SN_API_KEY, or configure SN_IMAGE_GEN_API_KEY only for an image-generation-specific override

  Some required environment variables are missing.
  Enter values below to save them to /path/to/.env.
  Press Enter to skip a variable.

  SN_API_KEY: <user input>

  ✅ Saved to /path/to/.env: SN_API_KEY
  🔄 Reloading environment...
  ✅ Environment reloaded successfully

=== Summary ===
✅ Environment is properly configured

If reload fails, the output will suggest restarting the agent:

  ✅ Saved to /path/to/.env: SN_API_KEY
  🔄 Reloading environment...
  ⚠️  Failed to reload environment: <error message>
  💡 Suggestion: Restart the agent to apply new configuration

Error Output

When checks fail:

=== SenseNova-Skills Environment Check ===

[1/3] Checking sn-image-base installation...
  ❌ sn-image-base directory not found
  Expected location: /path/to/skills/sn-image-base

[2/3] Checking Python dependencies...
  ❌ Missing packages: httpx, pillow
  Run: pip install -r skills/sn-image-base/requirements.txt

=== Summary ===
❌ Environment check failed
Please fix the errors above before using SenseNova-Skills.

Troubleshooting

sn-image-base Not Found

Problem: sn-image-base directory not found

Solution:

# Ensure you're in the project root
cd /path/to/SenseNova-Skills

# Verify the directory exists
ls -la skills/sn-image-base

Missing Dependencies

Problem: Required Python packages not installed

Solution:

# Install dependencies
pip install -r skills/sn-image-base/requirements.txt

# Or use a virtual environment
python -m venv .venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate
pip install -r skills/sn-image-base/requirements.txt

Missing Environment Variables

Problem: Required environment variables not set

Solution:

# If all capabilities use the same gateway, set only the global values.
export SN_API_KEY="your-api-key"
export SN_BASE_URL="https://your-api-endpoint.com"

# Or create a .env file
cat > .env << EOF
SN_API_KEY=your-api-key
SN_BASE_URL=https://token.sensenova.cn/v1
SN_CHAT_TYPE=openai-completions
SN_CHAT_MODEL=sensenova-6.8-flash-lite
EOF

# Load .env file
source .env  # Or use a tool like python-dotenv

Fallback priority is capability-specific variable > domain shared variable > global variable. For example, text calls use SN_TEXT_API_KEY -> SN_CHAT_API_KEY -> SN_API_KEY; vision calls use SN_VISION_API_KEY -> SN_CHAT_API_KEY -> SN_API_KEY; image generation uses SN_IMAGE_GEN_API_KEY -> SN_API_KEY.

API Connectivity Issues

Problem: Cannot reach API endpoints

Solution:

  1. Verify network connectivity

  2. Check firewall settings

  3. Verify API endpoint URLs are correct

  4. Test with curl:

    curl -I https://your-api-endpoint.com
    

Integration with Other Skills

This skill is designed to be run before using other skills in the SenseNova-Skills project:

# 1. Run doctor check
python skills/sn-image-doctor/scripts/check_environment.py

# 2. If checks pass, use other skills
python skills/sn-image-base/scripts/sn_agent_runner.py sn-image-generate \
    --prompt "A beautiful landscape"

Command-Line Options

OptionDescription
--verboseShow detailed diagnostic information
--helpShow help message

Exit Codes

CodeMeaning
0All checks passed
1One or more checks failed

See Also

  • sn-image-base/SKILL.md - Base-layer skill documentation
  • sn-image-base/references/api_spec.md - API specification
  • sn-infographic/SKILL.md - Example of a skill that depends on sn-image-base

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

Compare counts and shares for two categories in Excel data. The skill cleans the selected columns, calculates differences and percentages, and produces a summary spreadsheet plus bar and pie charts.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Comparing counts for two categories
  • Visualizing category shares
  • Cleaning merged-cell data before counting
OpenSenseNova/SenseNova-Skills5.9천2026년 10월 9일 업데이트

Analyze Excel data using custom categories, count distributions, and compare groups with charts. Score text using its length, technical terms, numbers, and selected complex concepts, then visualize difficulty levels and the relationship between text length and scores.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Summarize Excel records using custom categories
  • Compare category distributions across groups
  • Score and grade text using adjustable rules
OpenSenseNova/SenseNova-Skills5.9천2026년 10월 9일 업데이트

Count categories in a chosen data column after removing missing values and placeholder labels. Calculate each category’s share and create high-resolution charts combining counts, percentages, pie charts, and horizontal bars for distribution reports.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Compare record counts across categories
  • Show category shares with pie and bar charts
  • Exclude placeholder labels before counting
OpenSenseNova/SenseNova-Skills5.9천2026년 10월 9일 업데이트

Clean category and numeric fields in structured data, compare groups with counts and cross-tabulations, and produce charts, Excel results, and a Markdown report. Export visuals as high-resolution PNG and SVG files for use in reports.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Compare category distributions across groups
  • Clean category labels and fill merged-cell gaps
  • Export analysis results to Excel
OpenSenseNova/SenseNova-Skills5.9천2026년 10월 9일 업데이트

Filter Excel data using candidate column names, RGB color values, text prefixes, and regular expressions, which match text patterns. Calculate totals and averages, then export results to Excel with highlighted rows and a download link.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Filtering rows by RGB values or identifier prefixes
  • Converting text to numbers and calculating totals or averages
  • Extracting matching commands with their identifiers and descriptions
OpenSenseNova/SenseNova-Skills5.9천2026년 10월 9일 업데이트

Filter rows from Excel or previously converted Parquet files, a format designed for efficient data storage. Summarize matching records by group with counts, percentages, and totals, then export the summary to Excel.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Count records containing a specified risk level by work category
  • Calculate group shares among matching records
  • Summarize large datasets already converted to Parquet
OpenSenseNova/SenseNova-Skills5.9천2026년 10월 9일 업데이트

OpenSenseNova의 스킬 모두 보기

이 스킬의 문제 신고