Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/leiming2333/vision-toolkit/image-analysisnpx skills add leiming2333/Vision-Toolkit --skill image-analysisgit clone --depth 1 https://github.com/leiming2333/Vision-ToolkitWrote 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.
[](https://agentmods.dev/skills/leiming2333/vision-toolkit/image-analysis)<a href="https://agentmods.dev/skills/leiming2333/vision-toolkit/image-analysis"><img src="https://agentmods.dev/badge/skills/leiming2333/vision-toolkit/image-analysis.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00058 | $0.01818 |
| Opus 5 | $0.00029 | $0.00909 |
| Sonnet 5 | $0.00012 | $0.00364 |
| Haiku 4.5 | $0.00006 | $0.00182 |
Grade A, and why
image-analysis scanned grade A with 0 findings 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 3d ago.
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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 138 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Image Analysis
Understand an existing image by calling the standalone vision.py script in this project. Supports four operations: image description / visual QA, OCR (text extraction), object detection, and image similarity comparison. This skill is available to any agent and does not require the MCP server to be running — it calls the providers directly.
Relationship with the MCP vision tools
This project exposes image understanding through two entry points that share the same providers/ code and the same environment-variable configuration (API keys / endpoints / models):
- MCP tools (preferred) —
analyze_image,ocr,detect_objects,compare_images. Available when the MCP server is connected. Use them first. - This Skill (fallback) — a standalone script. Use it when:
- the MCP server is not connected / not running,
- the MCP tool call fails or times out,
- or you are in a context where only a Skill works (CI, batch, an agent without MCP).
Configuration source: the Skill reads the same environment variables as the MCP server (OPENAI_API_KEY / DASHSCOPE_API_KEY / GEMINI_API_KEY and the corresponding *_BASE_URL / *_VISION_MODEL). By default the Skill shares the MCP config — whatever the MCP server uses, the Skill uses too.
Skill-independent config (optional): the Skill also supports a separate config layer via SKILL_*-prefixed env vars. At runtime the Skill reads SKILL_<name> first; if unset it falls back to <name>. The MCP server does not read SKILL_* vars, so MCP behavior is unaffected. Set SKILL_* vars only when you want the Skill to use a different key / endpoint / model than MCP — e.g. SKILL_OPENAI_API_KEY, SKILL_OPENAI_BASE_URL, SKILL_OPENAI_VISION_MODEL, SKILL_DASHSCOPE_API_KEY, SKILL_QWEN_VL_MODEL, SKILL_GEMINI_API_KEY, SKILL_GEMINI_VISION_MODEL. If neither SKILL_* nor the shared key is set, tell the user to set the relevant environment variable.
The Skill script also has built-in provider auto-fallback: if the chosen provider fails, it automatically retries the other configured providers. So prefer the MCP tools first; if they fail, run this Skill script and it will try every available provider.
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.
- 3d ago First seen · 138 lines · 58 tokens per session scan A 38c9826d8b1d
image-analysis is a skill published in the GitHub repository leiming2333/Vision-Toolkit (1 stars, last pushed 20d ago), licensed MIT. It adds 58 tokens to every session and 1,818 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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