Best use case
image-review is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
用户说评价、改进、优化图片时触发。
Teams using image-review should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/image-review/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How image-review Compares
| Feature / Agent | image-review | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
用户说评价、改进、优化图片时触发。
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# image-review 用户说评价、改进、优化图片时触发。 ## 流程 ### Step 1: 检查最近图片 ```bash ls -lt /home/node/ai-outputs/ | head -5 ``` ### Step 2: 评估(5分制) 构图、色彩、细节、风格一致性、整体印象。 ### Step 3: 改进建议 评分<3.5时建议:prompt调整、换checkpoint、用hires workflow。 ### Step 4: 记录 ```bash python /home/node/.openclaw/workspace/tools/run-tracker.py --log "评估摘要" ```
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