vision-review

vision-review is a skill for Claude Code, Codex from MJorgin/dsh-media-skills. It costs 119 tokens per session (1,355 once invoked), scanned A, original, MIT.

A tool for reading images and checking screenshots, including text, layout, visual defects, watermarks, and logos.

In plain words
What is it for?
Reviewing screenshots, extracting image text, checking interfaces, and producing structured descriptions of image content.
Why use it?
It helps find problems that are difficult to detect from code alone, such as overlapping text, clipped content, or misplaced elements.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: reads ~/.codex paths; mentions Codex.

Good fit Reviewing screenshots, extracting image text, checking interfaces, and producing structured descriptions of image content.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/mjorgin/dsh-media-skills/vision-review
Install

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.

Any agent
npx skills add MJorgin/dsh-media-skills --skill vision-review
Clone the repo
git clone --depth 1 https://github.com/MJorgin/dsh-media-skills

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 vision-review

README.md
[![agentmods](https://agentmods.dev/badge/skills/mjorgin/dsh-media-skills/vision-review/github.svg)](https://agentmods.dev/skills/mjorgin/dsh-media-skills/vision-review)
Your own site
<a href="https://agentmods.dev/skills/mjorgin/dsh-media-skills/vision-review"><img src="https://agentmods.dev/badge/skills/mjorgin/dsh-media-skills/vision-review/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 vision-review

Your own site · 80×15
<a href="https://agentmods.dev/skills/mjorgin/dsh-media-skills/vision-review"><img src="https://agentmods.dev/badge/skills/mjorgin/dsh-media-skills/vision-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 119 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,355 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. 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: 2 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 3
    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 27
    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 $0.00119 $0.01355
Opus 5.5 $0.00048 $0.00542
Sonnet 5.5 $0.00024 $0.00271
Haiku 4.5 $0.00012 $0.00136

Measured 6d ago against content hash 610b8b2bd3cc, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

vision-review 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 6d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/vision.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.

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.

skills/vision-review/SKILL.md · 77 lines

How it starts

The opening of the file, as written. The whole thing — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Vision Review(读图 / OCR / 视觉检查)

用于显式视觉审查工作流:截图 QA、图片内容描述、OCR、水印/Logo 检测、界面布局问题检查,以及给程序化流程输出结构化证据。

DSH 桌面端 0.2.0-rc.2 / v0.1.6+ 兼容性:原生图片附件要求当前会话模型的 inputModalities 包含 image;默认 deepseek-flash 支持图片。纯文本模型会拒绝附件(MODEL_DOES_NOT_SUPPORT_IMAGES),不会触发旧版“自动转写成文字再喂给当前模型”的管道。此时可切换到视觉模型路由,或把本地图片路径传给本技能脚本进行审查。上游最新 tag dsh-v0.2.1-alpha.2 的源码仍保留这套 provider/附件契约。本技能适合需要脚本、故障转移链或 JSON 证据时使用。

用法

从本技能目录运行:

python3 scripts/vision.py <图片路径...> [--prompt="..."] [--provider=NAME] [--structured] [--doctor]

常用示例:

python3 scripts/vision.py screenshot.png
python3 scripts/vision.py a.png b.png --structured
python3 scripts/vision.py page.png --provider=siliconflow-qwen
python3 scripts/vision.py page.png --prompt="检查标题、按钮和图表是否重叠,并指出位置"
python3 scripts/vision.py --doctor

行为

  • 可一次传多张图;每张图会压缩成 JPEG,边长随批内张数自适应:1–2 张 1024px,3–4 张 768px,5 张 512px。
  • GLM-4V-Flash 单请求最多 5 张图;超过 5 张自动分批。
  • 默认 prompt 检查渲染完整性、文字重叠/溢出/错位、配色层次、水印和明显视觉 bug。
  • --structured 输出结构化 JSON:summary、ocr.full_text、layout.regions、semantics、visual、uncertainty;多批时输出 results 数组。
  • --provider=NAME 固定单个引擎,不做故障转移。可用名包括 zhipu-glm、deepseek、siliconflow-qwen、sensenova、gemini 和自定义 fallback 名称。
  • --doctor 检查 Pillow、已配置 key、候选模型和端点连通性。遇到引擎异常时先运行它。

引擎链

脚本按以下顺序尝试;可选引擎只有检测到对应 key 时才加入:

  1. 智谱 glm-4v-flash(主引擎,GLM_API_KEY;输出上限 1024)。
  2. DeepSeek 视觉模型(DEEPSEEK_API_KEY,付费可选;默认 deepseek-v4-flash-vision-exp,可用 DEEPSEEK_VISION_MODEL 覆盖)。
  3. SiliconFlow Qwen3-VL(SILICONFLOW_API_KEY;默认 Qwen/Qwen3-VL-8B-Instruct,可用 SILICONFLOW_VISION_MODEL 覆盖)。
  4. SenseNova(SENSENOVA_API_KEY;默认 sensenova-6.8-flash-lite,可用 SENSENOVA_VISION_MODEL 覆盖)。
  5. Gemini OpenAI-compatible endpoint(GEMINI_API_KEY;默认 gemini-3.6-flash,可用 GEMINI_MODEL 覆盖)。
  6. VISION_FALLBACKS 中声明的任意 OpenAI 兼容多模态引擎。

VISION_FALLBACKS 是 JSON 数组,每项包含 name、baseUrl、model,可选 apiKeyEnv、maxTokens、jsonObject。

密钥来源

按顺序读取:

  1. 进程环境变量;
  2. ~/.dsh/secrets/media-tools.env;
  3. ~/.codex/secrets/media-tools.env(历史兼容);
  4. ~/.dsh/.credentials.yaml 中的顶层 key 或 refs 子映射。

Read the full file on GitHub · 77 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. 6d ago Changed · +2 lines 610b8b2bd3cc
  2. 1mo ago Changed · +36 lines · -31 tokens per session a65acbbe25e7
  3. 2mo ago First seen · 39 lines · 150 tokens per session scan A 28186f0a0fd5

Subscribe to this mod's changes

vision-review is a skill published in the GitHub repository MJorgin/dsh-media-skills (25 stars, last pushed 3d ago), licensed MIT. It adds 119 tokens to every session and 1,355 once invoked, about $0.0005 per session on Opus 5.5. 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 2026-08-30.

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