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sn-image-doctor

Diagnose and fix SenseNova-Skills image environment setup with dependency and configuration validation.

2|Updated May 19, 2026
Search Tags:#image generation#dotenv#environment check#dependency validation#SenseNova#runtime health#config diagnostics
One-click install
npx skills add https://github.com/aiyinluya/SenseNova-Skills-Studio --skill sn-image-doctor-aiyinluya
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: sn-image-doctor
Source: https://github.com/aiyinluya/SenseNova-Skills-Studio/tree/main/skills/sn-image-doctor
Command: npx skills add https://github.com/aiyinluya/SenseNova-Skills-Studio --skill sn-image-doctor-aiyinluya

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

It helps you quickly detect missing SenseNova-Skills installation components, verify Python dependencies, and configure required environment variables so the image-generation skill stack can run reliably.

Core Features & Use Cases

  • Installation verification: Confirms that the required base-layer skill directory and key files (including SKILL.md, requirements, and runner script) exist.
  • Dependency validation: Checks the Python version and verifies that all packages listed in sn-image-base/requirements.txt can be imported.
  • Environment variable diagnostics + guided fixes: Uses sn-image-base Configs to validate configuration, prompts you for missing required variables, saves them to a .env file, reloads the environment, and suggests restarting the agent if needed.
  • Use Case: Before generating or composing office images, run this doctor to ensure SN_BASE_URL/SN_API_KEY (or capability-specific overrides like SN_IMAGE_GEN_API_KEY) are set correctly and that your runtime won’t fail later with avoidable configuration errors.

Quick Start

Run the doctor by executing the environment check script in skills/sn-image-doctor/scripts/check_environment.py.

Frequently Asked Questions about sn-image-doctor

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I fix SenseNova image generation environment setup errors?▼

To fix SenseNova image generation environment setup errors, run a diagnostic script that validates Python dependencies, checks base component directories, and interactively updates missing configuration variables in your .env file.

Why does my Python image generation script fail to import dependencies?▼

Your Python image generation script fails to import dependencies when packages listed in requirements.txt are missing or the Python version is below 3.9. Running environment checks verifies import readiness and installation integrity.

What environment variables do I need to configure for SenseNova image tasks?▼

For SenseNova image tasks, you must configure environment variables including SN_BASE_URL and SN_API_KEY, or capability-specific overrides like SN_IMAGE_GEN_API_KEY, saving them to a .env file to ensure reliable execution.

Can I validate my .env configuration before running image generation workflows?▼

You can validate your .env configuration before running image generation workflows by executing a pre-run health check that detects missing gateway variables and prompts you for interactive resolution to prevent runtime failures.

Do I need to install sn-image-base components before diagnosing my environment?▼

Yes, you need sn-image-base components installed before diagnosing your environment, because the validation process checks for required directories, verifies requirements.txt imports, and uses base configs to validate setup.

What is the best way to diagnose missing configuration variables for image generation?▼

The best way to diagnose missing configuration variables for image generation is executing an interactive environment check that validates configs, saves missing variables to a .env file, and reloads the environment to apply updates.

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