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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/zrt-ai-lab/opencode-skills --skill video-stickfigure- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads video-stickfigure automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
火柴人生图技能
🚨 核心原则
必须使用AI生图！禁止用PIL画线条！
检查标准：生成的图片文件 > 50KB
🔧 生图工具
使用 image-service skill：
python ~/.openclaw/skills/image-service/scripts/text_to_image.py "[prompt]" -r 9:16 -o stick1.png
📝 Prompt模板
深墨绿背景版（推荐·默认）
minimalist chalk-style stick figure on dark green chalkboard background #3c5b45,
white chalk line art, simple 5-stroke drawing style,
[动作描述],
exaggerated pose, hand-drawn feel, chalk texture,
no shading, no gradient, stark contrast,
vertical composition 9:16, no text, no watermark
纯黑背景版（备选）
minimalist stick figure, pure black background #000000,
white line art only, simple 5-stroke drawing,
[动作描述],
exaggerated pose, no shading, no gradient, no gray,
stark contrast, cartoon style,
vertical composition 9:16, no text, no watermark
选择建议：
- 深墨绿版：有黑板质感，视觉更柔和 ✅ 推荐
- 纯黑版：对比度更高，更简洁
动作描述 + 氛围元素（必须包含！）
火柴人不能孤零零的！必须加氛围元素来衬托情绪！
| 情绪/概念 | 人物动作 | 🌟 氛围元素（必加！） |
|---|---|---|
| 衰老/疲惫 | person slumped over, tired posture | + withered leaves falling, dim shadows, cracked ground |
| 枯萎/消沉 | person wilting like a dying plant | + dead tree nearby, falling petals, dark clouds |
| 向上/成长 | person climbing stairs upward | + sunlight rays from above, distant mountain peak, stars |
| 扛事/承担 | person lifting heavy weight overhead | + storm clouds, rain drops, lightning in background |
| 看远/远眺 | person standing on cliff, hand over eyes | + vast horizon, clouds below feet, sunrise glow |
| 容人/包容 | person with arms wide open | + small figures approaching, warm light rays, hearts floating |
| 愉悦/快乐 | person jumping with joy, arms raised | + confetti, sparkles, fireworks in sky |
| 成长/蜕变 | person breaking out of shell | + butterfly wings emerging, light beams, blooming flowers |
| 思考/沉思 | person sitting cross-legged, hand on chin | + floating question marks, gears, light bulb above head |
| 行动/奔跑 | person running forward with determination | + motion lines, wind effect, path stretching ahead |
Prompt组装公式
[基础模板] + [人物动作] + [氛围元素] + [后缀]
示例：衰老场景
minimalist chalk-style stick figure on dark green chalkboard background #3c5b45,
white chalk line art, simple 5-stroke drawing style,
person slumped over tired posture aging feeling,
withered leaves falling around, dim shadows, cracked ground beneath,
exaggerated pose, hand-drawn feel, chalk texture,
no shading, no gradient, stark contrast,
vertical composition 9:16, no text, no watermark
示例：爬台阶场景
minimalist chalk-style stick figure on dark green chalkboard background #3c5b45,
white chalk line art, simple 5-stroke drawing style,
person climbing stairs upward with determination,
sunlight rays streaming from above, distant mountain peak visible, glowing stars,
exaggerated pose, hand-drawn feel, chalk texture,
no shading, no gradient, stark contrast,
vertical composition 9:16, no text, no watermark
⚠️ 氛围元素规则
- 必须添加 - 不加氛围元素的火柴人图太单调
- 与情绪匹配 - 消极情绪用暗元素，积极情绪用亮元素
- 不要太多 - 2-3个氛围元素足够，太多会杂乱
- 保持简约 - 氛围元素也是粉笔画风格，不要写实
🎨 HSV背景统一处理（必做！）
AI无法精确控制颜色！生图后必须用代码统一背景色！
处理脚本
import cv2
import numpy as np
def unify_background_hsv(input_path, output_path, target_hex="#3c5b45"):
"""
用HSV范围替换统一背景色
"""
img = cv2.imread(input_path)
hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
# 绿色系HSV范围（覆盖AI生成的各种绿色）
lower = np.array([35, 20, 20])
upper = np.array([85, 255, 255])
# 创建掩码
mask = cv2.inRange(hsv, lower, upper)
# 目标颜色 BGR
target_bgr = tuple(int(target_hex.lstrip('#')[i:i+2], 16) for i in (4, 2, 0))
# 替换背景
result = img.copy()
result[mask > 0] = target_bgr
cv2.imwrite(output_path, result)
return output_path
# 批量处理
import glob
for f in glob.glob("stick*.png"):
if "_unified" not in f:
out = f.replace(".png", "_unified.png")
unify_background_hsv(f, out)
print(f"处理完成: {out}")
命令行版本
python3 << 'EOF'
import cv2
import numpy as np
import glob
import sys
target_hex = "#3c5b45"
target_bgr = tuple(int(target_hex.lstrip('#')[i:i+2], 16) for i in (4, 2, 0))
for f in glob.glob("stick*.png"):
if "_unified" in f:
continue
img = cv2.imread(f)
hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
mask = cv2.inRange(hsv, np.array([35,20,20]), np.array([85,255,255]))
result = img.copy()
result[mask > 0] = target_bgr
out = f.replace(".png", "_unified.png")
cv2.imwrite(out, result)
print(f"✅ {f} -> {out}")
EOF
✅ 检查清单（必须全部通过！）
在交付图片前，必须确认：
| 检查项 | 标准 | 不通过则 |
|---|---|---|
| 文件大小 | 每张 > 50KB | 重新AI生图 |
| 图片数量 | 与场景数量一致 | 补充生成 |
| 背景颜色 | 统一为 #3c5b45 | 执行HSV处理 |
| 火柴人可见 | 白色线条清晰 | 重新生成 |
# 快速检查文件大小
ls -la stick*_unified.png | awk '{if($5<50000) print "❌ "$9" 太小: "$5"B"; else print "✅ "$9": "$5"B"}'
📁 输出规范
| 文件 | 说明 |
|---|---|
| stick1.png, stick2.png, ... | AI生成的原始图片 |
| stick1_unified.png, ... | HSV处理后的统一背景图片 |
后续流程只使用 *_unified.png 文件！
🚫 常见错误
| 错误 | 后果 | 正确做法 |
|---|---|---|
| 用PIL画线条 | 视频看起来像测试图 | 用image-service AI生图 |
| 跳过HSV处理 | 背景色深浅不一 | 必须执行HSV统一 |
| 文件<50KB | 图片质量差 | 重新生成 |
| 用原图不用unified | 背景不统一 | 只用_unified.png |
| 火柴人没有氛围元素 | 画面单调无感染力 | prompt必须加氛围元素 |
FAQ
What does the video-stickfigure skill do?
火柴人图片生成技能。使用AI生成粉笔画风格火柴人，并用HSV统一背景色。当需要生成火柴人视频素材时触发。
How do I install video-stickfigure?
Run npx skills add https://github.com/zrt-ai-lab/opencode-skills --skill video-stickfigure in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/video-stickfigure/ (personal) or .claude/skills/video-stickfigure/ (project).
Which AI agents can use video-stickfigure?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is video-stickfigure safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains video-stickfigure?
It is published by zrt-ai-lab in zrt-ai-lab/opencode-skills. It has 49 recorded installs.
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