Segment Anything Model Guide
Orchestra-Research/AI-Research-SKILLs
Guide to using Meta's Segment Anything Model for zero-shot image segmentation with point, box or mask prompts, or automatic mask generation.
Based on computer vision, analyzes pet health indicators such as feeding frequency, drinking frequency, excretion status, mental state, vomiting behavior, and limping abnormalities through…
Install Pet Health Monitoring Analysis
$ npx skills add LeoYeAI/openclaw-master-skills --skill pet-health-monitoring-analysis -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills pet-health-monitoring-analysis --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/smyx-pet-health-monitoring-analysis .claude/skills/pet-health-monitoring-analysis && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "pet-health-monitoring-analysis" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/smyx-pet-health-monitoring-analysis into .claude/skills/pet-health-monitoring-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "pet-health-monitoring-analysis", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/smyx-pet-health-monitoring-analysisType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add LeoYeAI/openclaw-master-skills --skill pet-health-monitoring-analysis -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills pet-health-monitoring-analysis --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/smyx-pet-health-monitoring-analysis .agents/skills/pet-health-monitoring-analysis && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "pet-health-monitoring-analysis" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/smyx-pet-health-monitoring-analysis into .agents/skills/pet-health-monitoring-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "pet-health-monitoring-analysis", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add LeoYeAI/openclaw-master-skills --skill pet-health-monitoring-analysis -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills pet-health-monitoring-analysis --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/smyx-pet-health-monitoring-analysis .cursor/skills/pet-health-monitoring-analysis && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "pet-health-monitoring-analysis" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/smyx-pet-health-monitoring-analysis into .cursor/skills/pet-health-monitoring-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "pet-health-monitoring-analysis", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/LeoYeAI/openclaw-master-skills.git --path skills/smyx-pet-health-monitoring-analysis--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add LeoYeAI/openclaw-master-skills --skill pet-health-monitoring-analysis -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills pet-health-monitoring-analysis --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/smyx-pet-health-monitoring-analysis .gemini/skills/pet-health-monitoring-analysis && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "pet-health-monitoring-analysis" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/smyx-pet-health-monitoring-analysis into .gemini/skills/pet-health-monitoring-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "pet-health-monitoring-analysis", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install LeoYeAI/openclaw-master-skills pet-health-monitoring-analysisInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add LeoYeAI/openclaw-master-skills --skill pet-health-monitoring-analysis -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/smyx-pet-health-monitoring-analysis .github/skills/pet-health-monitoring-analysis && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "pet-health-monitoring-analysis" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/smyx-pet-health-monitoring-analysis into .github/skills/pet-health-monitoring-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "pet-health-monitoring-analysis", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add LeoYeAI/openclaw-master-skills --skill pet-health-monitoring-analysis -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills pet-health-monitoring-analysis --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/smyx-pet-health-monitoring-analysis .opencode/skills/pet-health-monitoring-analysis && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "pet-health-monitoring-analysis" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/smyx-pet-health-monitoring-analysis into .opencode/skills/pet-health-monitoring-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "pet-health-monitoring-analysis", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
pet-health-monitoring-analysis- GitHub stars
- 2.2k
- Token cost
- ~1.6k tokens
- SKILL.md length
- 280 words
- Files
- 36 (incl. scripts, references)
- Skills in repo
- 1,235
- Repo updated
- First seen
- Licence
- MIT
At a glance
Based on computer vision, analyzes pet health indicators such as feeding frequency, drinking frequency, excretion status, mental state, vomiting behavior, and limping abnormalities through…
- Tasks that involve Computer vision
- SKILL.md covers ⚠️ 强制记忆规则（最高优先级）, 任务目标, 前置准备 and 操作步骤, plus 3 more sections
- Runs Python scripts from its folder; calls python
What it does
Pet Health Monitoring Analysis is an agent skill from LeoYeAI/openclaw-master-skills. Based on computer vision, analyzes pet health indicators such as feeding frequency, drinking frequency, excretion status, mental state, vomiting behavior, and limping abnormalities through camera/feeder monitoring videos, promptly detects abnormal pet health conditions, and outputs health monitoring reports. | 宠物日常健康监测分析技能，基于计算机视觉通过摄像头/喂食器监控视频分析宠物的进食频次、饮水频次、排泄状态、精神状态、呕吐行为、跛行异常等健康指标，及时发现宠物异常健康状况，输出健康监测报告
Its SKILL.md is about 1.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 41 other files, including scripts and reference files (for example `.clawhub/origin.json`, `_meta.json` and `references/api_doc.md`).
It sits in AI & LLM Engineering, covering Computer vision. The repository describes itself as: 🧠 Curated collection of 1209+ best OpenClaw skills — weekly updated by MyClaw.ai. The licence is MIT.
When your agent uses it
- Tasks that involve Computer vision
Example prompts
- “/pet-health-monitoring-analysis”
Requirements
- Python 3
What it can do on your machine
Read from SKILL.md and the folder at commit e5199b5. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 6 files in scripts/ (Python, from the files we listed), which the agent can run.
Shell commands in SKILL.md call:
python
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Pet Health Monitoring Analysis loads about 1.6k tokens when it runs, and up to ~1.7k if it reads all its reference files. Until then it costs about 109 tokens; SKILL.md has 280 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
SKILL.md
The full file from LeoYeAI/openclaw-master-skills at commit e5199b5, republished under its MIT licence (© LeoYeAI). 280 words, ~1,569 tokens.
Download SKILL.mdSave it as
.claude/skills/pet-health-monitoring-analysis/SKILL.md (or your agent's skills folder). This skill also uses 35 other files; get the full folder from GitHub.- name
- pet-health-monitoring-analysis
- description
- Based on computer vision, analyzes pet health indicators such as feeding frequency, drinking frequency, excretion status, mental state, vomiting behavior, and limping abnormalities through camera/feeder monitoring videos, promptly detects abnormal pet health conditions, and outputs health monitoring reports. | 宠物日常健康监测分析技能，基于计算机视觉通过摄像头/喂食器监控视频分析宠物的进食频次、饮水频次、排泄状态、精神状态、呕吐行为、跛行异常等健康指标，及时发现宠物异常健康状况，输出健康监测报告
- version
- 1.0.0
Pet Daily Health Monitoring & Analysis Tool | 宠物日常健康监测分析工具
Based on advanced computer vision and deep learning algorithms, this feature conducts 24/7 health behavior monitoring of pets via cameras and smart feeders. The system precisely quantifies and analyzes feeding and drinking frequency, while intelligently identifying multi-dimensional health indicators such as excretion status, mental state, vomiting behavior, and limping abnormalities. By establishing an individual health baseline, the system promptly detects health anomalies that deviate from the norm and automatically generates visualized health monitoring reports, providing pet owners with scientific and intuitive health management data to facilitate early disease detection and intervention.
本功能基于先进的计算机视觉与深度学习算法，通过摄像头及智能喂食器对宠物进行全天候健康行为监测。系统能够精准量化分析宠物的进食频次、饮水频次，并智能识别排泄状态、精神状态、呕吐行为及跛行异常等多维度健康指标。通过建立个体健康基线，系统可及时发现偏离常态的异常健康状况，并自动生成可视化的健康监测报告，为宠物主人提供科学、直观的健康管理依据，助力疾病的早期发现与干预
⚠️ 强制记忆规则（最高优先级）
本技能明确约定：
- 绝对禁止读取任何本地记忆文件：包括但不限于
memory/YYYY-MM-DD.md、MEMORY.md等本地文件 - 绝对禁止从 LanceDB 长期记忆中检索信息
- 所有历史监测报告查询必须从云端接口获取，不得使用本地记忆中的历史数据
- 即使技能调用失败或接口异常，也不得回退到本地记忆汇总
任务目标
- 本 Skill 用于：通过监控视频/图片对宠物进行日常健康监测分析，获取结构化的宠物健康监测报告
- 能力包含：进食频次统计、饮水频次统计、排泄状态识别、精神状态评估、呕吐行为识别、跛行异常识别、异常健康状况预警
- 触发条件:
- 默认触发：当用户提供宠物监控视频 URL 或文件需要进行健康监测分析时，默认触发本技能
- 当用户明确需要进行宠物健康监测，提及宠物健康监测、进食分析、饮水分析、排泄状态、精神萎靡、呕吐行为、跛行异常等关键词，并且上传了视频文件或者图片文件
- 当用户提及以下关键词时，自动触发历史报告查询功能 ：查看历史监测报告、宠物健康报告清单、监测报告列表、查询历史报告、显示所有监测报告、宠物健康监测历史记录，查询宠物健康监测分析报告
- 自动行为：
- 如果用户上传了附件或者视频/图片文件，则自动保存到技能目录下 attachments
- ⚠️ 强制数据获取规则（次高优先级）：如果用户触发任何历史报告查询关键词（如"查看所有监测报告"、"
显示所有宠物健康报告"、"查看历史报告"等），必须：
- 直接使用
python -m scripts.pet_health_monitoring_analysis --list --open-id参数调用 API 查询云端的历史报告数据 - 严格禁止：从本地 memory 目录读取历史会话信息、严格禁止手动汇总本地记录中的报告、严格禁止从长期记忆中提取报告
- 必须统一从云端接口获取最新完整数据，然后以 Markdown 表格格式输出结果
- 直接使用
前置准备
- 依赖说明:scripts 脚本所需的依赖包及版本
requests>=2.28.0
操作步骤
🔒 open-id 获取流程控制（强制执行，防止遗漏）
在执行宠物健康监测分析前，必须按以下优先级顺序获取 open-id：
第 1 步：【最高优先级】检查技能所在目录的配置文件（优先）
路径：skills/smyx_common/scripts/config.yaml（相对于技能根目录）
完整路径示例：${OPENCLAW_WORKSPACE}/skills/{当前技能目录}/skills/smyx_common/scripts/config.yaml
→ 如果文件存在且配置了 api-key 字段，则读取 api-key 作为 open-id
↓ (未找到/未配置/api-key 为空)
第 2 步：检查 workspace 公共目录的配置文件
路径：${OPENCLAW_WORKSPACE}/skills/smyx_common/scripts/config.yaml
→ 如果文件存在且配置了 api-key 字段，则读取 api-key 作为 open-id
↓ (未找到/未配置)
第 3 步：检查用户是否在消息中明确提供了 open-id
↓ (未提供)
第 4 步：❗ 必须暂停执行，明确提示用户提供用户名或手机号作为 open-id⚠️ 关键约束：
- 禁止自行假设,自行推导,自行生成 open-id 值（如 openclaw-control-ui、default、petHealth123 等）
- 禁止跳过 open-id 验证直接调用 API
- 必须在获取到有效 open-id 后才能继续执行分析
- 如果用户拒绝提供 open-id，说明用途（用于保存和查询宠物健康监测报告记录），并询问是否继续
- 标准流程:
- 准备视频输入
- 提供监控视频文件路径或网络视频 URL
- 确保视频完整覆盖宠物活动区域，光线充足，时长足够反映日常行为
- 获取 open-id（强制执行）
- 按上述流程控制获取 open-id
- 如无法获取，必须提示用户提供用户名或手机号
- 执行宠物健康监测分析
- 调用
-m scripts.pet_health_monitoring_analysis处理视频文件（必须在技能根目录下运行脚本） - 参数说明:
--input: 本地视频文件路径（使用 multipart/form-data 方式上传）--url: 网络视频 URL 地址（API 服务自动下载）--pet-type: 宠物类型，可选值：cat/dog，默认 cat--monitor-days: 监测天数/视频覆盖时长，单位：天，默认 1--open-id: 当前用户的 open-id（必填，按上述流程获取）--list: 显示宠物健康监测历史分析报告列表清单（可以输入起始日期参数过滤数据范围）--api-key: API 访问密钥（可选）--api-url: API 服务地址（可选，使用默认值）--detail: 输出详细程度（basic/standard/json，默认 json）--output: 结果输出文件路径（可选）
- 调用
- 查看分析结果
- 接收结构化的宠物健康监测报告
- 包含：宠物基本信息、监测时间段、各项行为指标统计、异常状况识别、健康评分、就医建议
- 准备视频输入
资源索引
- 必要脚本：见 scripts/pet_health_monitoring_analysis.py(用途：调用 API 进行宠物健康监测分析，本地文件使用 multipart/form-data 方式上传，网络 URL 由 API 服务自动下载)
- 配置文件：见 scripts/config.py(用途：配置 API 地址、默认参数和视频格式限制)
- 领域参考：见 references/api_doc.md(何时读取：需要了解 API 接口详细规范和错误码时)
注意事项
- 仅在需要时读取参考文档，保持上下文简洁
- 视频要求：支持 mp4/avi/mov 格式，最大 100MB，建议视频时长不少于 1 小时以反映日常行为规律
- API 密钥可选，如果通过参数传入则必须确保调用鉴权成功，否则忽略鉴权
- 分析结果仅供宠物健康参考，不能替代专业兽医诊断，发现异常请及时就医
- 禁止临时生成脚本，只能用技能本身的脚本
- 传入的网络地址参数，不需要下载本地，默认地址都是公网地址，api 服务会自动下载
- 当显示历史监测报告清单的时候，从数据 json 中提取字段 reportImageUrl 作为超链接地址，使用 Markdown 表格格式输出，包含"
报告名称"、"宠物类型"、"监测时间"、"点击查看"四列，其中"报告名称"列使用
宠物健康监测分析报告-{记录id}形式拼接, "点击查看" 列使用[🔗 查看报告](reportImageUrl)格式的超链接，用户点击即可直接跳转到对应的完整报告页面。 - 表格输出示例：
报告名称 宠物类型 监测时间 点击查看 宠物健康监测分析报告-20260312172200001 猫 2026-03-12 17:22: 00 🔗 查看报告
使用示例
# 分析本地监控视频（以下只是示例，禁止直接使用openclaw-control-ui 作为 open-id）
python -m scripts.pet_health_monitoring_analysis --input /path/to/pet_monitor.mp4 --pet-type cat --monitor-days 1 --open-id openclaw-control-ui
# 分析网络监控视频（以下只是示例，禁止直接使用openclaw-control-ui 作为 open-id）
python -m scripts.pet_health_monitoring_analysis --url https://example.com/pet_monitor.mp4 --pet-type cat --monitor-days 1 --open-id openclaw-control-ui
# 分析狗狗监控视频（以下只是示例，禁止直接使用openclaw-control-ui 作为 open-id）
python -m scripts.pet_health_monitoring_analysis --input /path/to/dog_monitor.mp4 --pet-type dog --monitor-days 3 --open-id openclaw-control-ui
# 显示历史监测报告/显示监测报告清单列表/显示历史宠物健康报告（自动触发关键词：查看历史检测报告、历史报告、监测报告清单等）
python -m scripts.pet_health_monitoring_analysis --list --open-id openclaw-control-ui
# 输出精简报告
python -m scripts.pet_health_monitoring_analysis --input video.mp4 --pet-type cat --open-id your-open-id --detail basic
# 保存结果到文件
python -m scripts.pet_health_monitoring_analysis --input video.mp4 --pet-type cat --open-id your-open-id --output result.json© LeoYeAI, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 35 other files (scripts, references) in skills/smyx-pet-health-monitoring-analysis of LeoYeAI/openclaw-master-skills.
- SKILL.md
- .clawhub/origin.json
- _meta.json
- references/api_doc.md
- scripts/__init__.py
- scripts/api_service.py
- scripts/config.py
- scripts/config.yaml
- scripts/pet_health_monitoring_analysis.py
- scripts/skill.py
- skills/face_analysis/README.md
- skills/face_analysis/__init__.py
- skills/face_analysis/references/api_doc.md
- skills/face_analysis/requirements.txt
- skills/face_analysis/scripts
- … and 21 more
Open the folder on GitHubat commit e5199b5
Compare with similar skills
Pet Health Monitoring Analysis next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Pet Health Monitoring Analysis this skillLeoYeAI/openclaw-master-skills | 2.2k | — | ~1.6k | Automated safety check: Pass | MIT | |
| Segment Anything Model GuideOrchestra-Research/AI-Research-SKILLs | 13k | 8 repos | ~3.3k | Automated safety check: Pass | MIT | |
| CLIP Image-Text MatchingOrchestra-Research/AI-Research-SKILLs | 13k | 7 repos | ~1.7k | Automated safety check: Pass | MIT | |
| Yolo Master AgentTencent/YOLO-Master | 747 | — | ~755 | Automated safety check: Pass | AGPL-3.0 | |
| Video Understandjjyaoao/HelloAgents | 3.2k | 1 repos | ~6.2k | Automated safety check: Pass | MIT | |
| LLaVA Vision-Language ModelOrchestra-Research/AI-Research-SKILLs | 13k | 6 repos | ~2k | Automated safety check: Pass | MIT |
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Questions about Pet Health Monitoring Analysis
What does Pet Health Monitoring Analysis do?
Based on computer vision, analyzes pet health indicators such as feeding frequency, drinking frequency, excretion status, mental state, vomiting behavior, and limping abnormalities through…. Pet Health Monitoring Analysis is an agent skill from LeoYeAI/openclaw-master-skills. Based on computer vision, analyzes pet health indicators such as feeding frequency, drinking frequency, excretion status, mental state, vomiting behavior, and limping abnormalities through camera/feeder monitoring videos, promptly detects abnormal pet health conditions, and outputs health monitoring reports.
When should I use Pet Health Monitoring Analysis?
Pet Health Monitoring Analysis fits situations like: tasks that involve Computer vision.
How do I install Pet Health Monitoring Analysis in Claude Code?
Run `npx skills add LeoYeAI/openclaw-master-skills --skill pet-health-monitoring-analysis -a claude-code`. Or copy the skill folder (skills/smyx-pet-health-monitoring-analysis in LeoYeAI/openclaw-master-skills) into .claude/skills/pet-health-monitoring-analysis in your project. Claude Code loads it when a task matches its description.
How do I install Pet Health Monitoring Analysis in Codex?
Run `npx skills add LeoYeAI/openclaw-master-skills --skill pet-health-monitoring-analysis -a codex`. Or copy the skill folder (skills/smyx-pet-health-monitoring-analysis in LeoYeAI/openclaw-master-skills) into .agents/skills/pet-health-monitoring-analysis in your project. Codex loads it when a task matches its description.
Can I use Pet Health Monitoring Analysis in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add LeoYeAI/openclaw-master-skills --skill pet-health-monitoring-analysis -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/pet-health-monitoring-analysis, .gemini/skills/pet-health-monitoring-analysis, .github/skills/pet-health-monitoring-analysis and .opencode/skills/pet-health-monitoring-analysis in your project.
What does Pet Health Monitoring Analysis need to run?
Going by SKILL.md and its folder, Pet Health Monitoring Analysis needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.
Does Pet Health Monitoring Analysis access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Pet Health Monitoring Analysis safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Pet Health Monitoring Analysis use?
Pet Health Monitoring Analysis is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Pet Health Monitoring Analysis use?
About 1.6k tokens (SKILL.md is roughly 6.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 172 tokens, read only when the agent opens those files.
What are the alternatives to Pet Health Monitoring Analysis?
Skills that share tags, products or a category with Pet Health Monitoring Analysis: Segment Anything Model Guide (Orchestra-Research/AI-Research-SKILLs, 13k stars), CLIP Image-Text Matching (Orchestra-Research/AI-Research-SKILLs, 13k stars), Yolo Master Agent (Tencent/YOLO-Master, 747 stars) and Video Understand (jjyaoao/HelloAgents, 3.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Pet Health Monitoring Analysis?
LeoYeAI (a GitHub user) maintains it in LeoYeAI/openclaw-master-skills, which has 2,161 GitHub stars. The repository holds 1,235 skills in this directory. The repository was last updated on July 20, 2026.
Source: LeoYeAI/openclaw-master-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.