sn-image-doctor

sn-image-doctor is a skill for Claude Code, Codex from OpenSenseNova/SenseNova-Skills. It costs 63 tokens per session (1,316 once invoked), scanned A, original, MIT.

A diagnostic tool that checks whether the SenseNova image tools, Python packages, and required environment settings are available.

In plain words
What is it for?
Checking installation, dependencies, and environment variables for the SenseNova image-generation system.
Why use it?
It finds setup problems before image-related skills run and can guide configuration of missing API keys.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is python skills/sn-image-base/scripts/sn_agent_runner.py sn-image-generate \.

Good fit Checking installation, dependencies, and environment variables for the SenseNova image-generation system.

Compare 6 skills from other repositories ↓
About the project

SenseNova-Skills is a collection of modular skills that extend SenseNova models with office-assistant capabilities such as image generation, presentation creation, spreadsheet analysis, and research. The skills are designed for use in agent runtimes and can be combined into productivity workflows; the catalogue entries are individual skills and agents from this collection.

OpenSenseNova/SenseNova-Skills · 5,570 stars · on GitHub

Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo
git clone --depth 1 https://github.com/OpenSenseNova/SenseNova-Skills
agentmods
npx agentmods add skills/opensensenova/sensenova-skills/sn-image-doctor

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for sn-image-doctor

README.md
[![agentmods](https://agentmods.dev/badge/skills/opensensenova/sensenova-skills/sn-image-doctor/github.svg)](https://agentmods.dev/skills/opensensenova/sensenova-skills/sn-image-doctor)
Your own site
<a href="https://agentmods.dev/skills/opensensenova/sensenova-skills/sn-image-doctor"><img src="https://agentmods.dev/badge/skills/opensensenova/sensenova-skills/sn-image-doctor/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for sn-image-doctor

Your own site · 80×15
<a href="https://agentmods.dev/skills/opensensenova/sensenova-skills/sn-image-doctor"><img src="https://agentmods.dev/badge/skills/opensensenova/sensenova-skills/sn-image-doctor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 63 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,316 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 5 findings, up to high

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • high Privilege Escalation · line 7
    Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.
    Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
  • high Privilege Escalation · line 151
    Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.
    Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
  • high Privilege Escalation · line 152
    Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.
    Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
  • high Privilege Escalation · line 159
    Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.
    Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
  • high Privilege Escalation · line 160
    Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.
    Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00063 $0.01316
Opus 5 $0.00032 $0.00658
Sonnet 5 $0.00013 $0.00263
Haiku 4.5 $0.00006 $0.00132

Measured 4d ago against content hash 067d0d9d470c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

sn-image-doctor scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/check_environment.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

4. Test with curl:
skills/sn-image-doctor/SKILL.md · 212 lines

How it starts

The opening of the file, as written. The whole thing — 212 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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.

Read the full file on GitHub · 212 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 4d ago Changed 067d0d9d470c
  2. 9d ago First seen · 212 lines · 63 tokens per session scan A 2064bb4e7a06

Subscribe to this mod's changes

sn-image-doctor is a skill published in the GitHub repository OpenSenseNova/SenseNova-Skills (5,570 stars, last pushed yesterday), licensed MIT. It adds 63 tokens to every session and 1,316 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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