| name | hermes-external-skill-install |
| description | Install pre-built external AI agent skills from GitHub (agentskills.io / Claude Code / OpenClaw ecosystem) directly into Hermes Agent's skills directory.
Two methods: (1) `npx skills add` (agentskills.io CLI) — fast but may fail on format, (2) `git clone` fallback — always works, preserves subdirectory skills and assets.
Use when the user says "装一下这个skill", "安装这个技能", "装个XX", "install this skill", or points to a GitHub repo that contains a SKILL.md. |
Hermes 外部 Tool/Skill 安装工作流
Install external tools or skills from GitHub repos into Hermes. Covers two distinct cases:
- Case A (pure skill): Repos that are just SKILL.md + references — install directly into Hermes skills directory
- Case B (tool-with-skill): Full AI application repos that happen to have a SKILL.md — they need their own dev directory, dependency installation, system requirement verification, API key setup, and THEN symlink into Hermes as a skill
触发条件
- 用户指向一个 GitHub 仓库并要求安装（"装一下这个skill"、"安装xx"、"装一下祂"、"install the skill from github.com/...", "看看这个" → "你先安装一下祂"）
- 仓库包含
SKILL.md
- 用户提到
npx skills add 或 skills add 但命令失败
- 用户问"这些 skill 从哪来的"、"给其他 agent 也装这些" → 先查
references/hermes-management-skills.md 获取已知来源
- 用户问"ClawHub 里有没有 X" → 直接
clawhub search + 参考 references/clawhub-toon-example.md 里的评估矩阵模式
决策分支: Pure Skill vs Tool-with-Skill vs npm-Package Skill Generator
Before proceeding, classify the source:
| Signal | Pure Skill (Case A) | Tool-with-Skill (Case B) | npm-Package Generator (Case C) | ClawHub Skill (Case D) |
|---|
| Source format | GitHub repo URL | GitHub repo URL | npm install -g @scope/package | clawhub search <query> then clawhub install <slug> |
Has SKILL.md directly | ✅ Yes | ✅ Yes (within repo) | ❌ No — CLI generates SKILL.md files | ✅ Yes (in registry) |
Has pyproject.toml / package.json | ❌ No | ✅ Yes | ✅ Yes (the npm package itself) | ⚠️ Optional — some are pure docs, some bundle scripts |
| Has system deps | ❌ Minimal | ✅ Yes (ffmpeg, brew, etc.) | ⚠️ May need companion tools (e.g., openspec CLI) | ⚠️ Variable — check scripts/ field on hub page |
| Workflow | Clone SKILL.md | Clone app + install deps + symlink | npm install -g → tool init → copy generated skills | clawhub search → evaluate → clawhub install <slug> (and possibly copy bundled scripts to PATH) |
| Example | alchaincyf/nuwa-skill | browser-use/video-use | @rpamis/comet (generates 28 platform skill sets) | @bonk-moltbot/toon, @zmkkevin/toon-json |
Decision rule: If the user points to an npm package name (or gives a GitHub repo for an npm package) that is a CLI generating SKILL.md files for multiple AI coding platforms, treat as Case C.
Decision rule (D): If the user says "找一下有没有 X skill" / "看看有没有装 X" / "装个 X skill" without naming a specific repo, and ClawHub is the installed marketplace CLI (clawhub --version to confirm), use Case D. Always evaluate multiple candidates before installing — the top-rated search hit is not always the right one. See Case D section below.
Case D: ClawHub Skill Discovery & Evaluation
For users who ask "有没有 X skill" or want to browse the registry without naming a specific repo. ClawHub is the official OpenClaw skill marketplace.
D0: Confirm ClawHub is installed
clawhub --version
If not installed: npm install -g @openclaw/clawhub (Case C workflow).
D1: Search — only one command works
Pitfall: clawhub info <slug> does NOT exist. The CLI only has: search, install, update, uninstall, list, pin, unpin, login, logout, whoami, auth. Running clawhub info foo bar returns a usage error every time.
clawhub search <query>
clawhub info <slug>
The search output is a vertical list with author, name, and a relevance-style score:
- Searching
toon @bonk-moltbot Toon (3.690)
toon-adoption-skill @nelohenriq TOON (2.515)
toon-json @zmkkevin Shrink JSON in Prompts (TOON Encoder/Decoder) (2.513)
toonany @casperkwok Toonany (1.490)
D2: Evaluate candidates — the matrix pattern
The top hit by score is not always the right one. Pull each candidate's hub page and build a matrix before deciding.
Pitfall: The hub URL is https://hub.openclaw.ai/<author>/<slug>, NOT clawhub.dev (returns 404 / fetch errors) and NOT clawhub.ai (different page).
web_extract urls=["https://hub.openclaw.ai/<author>/<slug>"]
Compare on at least these axes:
| Axis | What to check | Why it matters |
|---|
| Positioning | What is the skill FOR? (encoding tool / spec doc / pipe wrapper / SDK binding) | A pure spec doc with no scripts gives the agent nothing to run |
| Spec version | If the skill claims a version (e.g., "TOON v1") and a reference SDK exists with a different version (e.g., @toon-format/toon v3.3), flag the mismatch | Round-trip may fail silently |
| Implementation | Bundled script? Wraps official CLI? Or pure docs? | Pure docs → agent has to write code each time → unreliable |
| Dependency | Self-contained / needs npx / needs Python / needs system binary | Drives install path |
| Reliability | Author's track record, last updated, recent commits | Stale = likely broken against latest deps |
| Hermes fit | Does installing give me a SKILL.md I can read, a script in PATH I can run, or both? | clawhub install puts things in skills/, NOT bin/ |
Decision rule of thumb:
- If multiple candidates exist, prefer the one using the official upstream CLI/SDK over independent reimplementations (avoids version drift).
- Prefer a skill that exposes a runnable command over one that just teaches the agent the syntax.
- Avoid "pure teaching" skills (
xxx-adoption, xxx-guide) unless the agent already has a reliable encoder/decoder to use.
D3: Install — and copy bundled scripts to PATH
clawhub install <slug>
Pitfall (CRITICAL): clawhub install <slug> puts the SKILL.md and bundled files in ~/.hermes/skills/<dir>/<slug>/. It does NOT copy any executable scripts into ~/.local/bin or anywhere on $PATH. For skills whose value is a wrapper script (e.g., @bonk-moltbot/toon ships scripts/toon which wraps npx @toon-format/cli), install alone is insufficient.
Empty-shell trap (verified 2026-07-12): A ClawHub skill's SKILL.md may describe a scripts/<bin> wrapper without shipping one. clawhub install @bonk-moltbot/toon produced a package containing only _meta.json, SKILL.md, skill-card.md, .clawhub/origin.json — zero executable files. The README said "Copy script to PATH: cp scripts/toon ~/.local/bin/" but scripts/ didn't exist. Always verify before recommending the install path:
ls ~/.hermes/skills/<dir>/<slug>/scripts/ 2>/dev/null | head
If the script does exist, copy + chmod + verify:
cp ~/.hermes/skills/<dir>/<slug>/scripts/<bin> ~/.local/bin/
chmod +x ~/.local/bin/<bin>
command -v <bin>
If ~/.local/bin isn't on the user's $PATH (Hermes TUI launches from fish via .bashrc — verify with echo $PATH | tr ':' '\n' | grep local/bin), symlink into a PATH dir that IS populated:
ln -sf ~/.hermes/skills/<dir>/<slug>/scripts/<bin> ~/.npm-global/bin/<bin>
When the skill is empty-shell but the underlying SDK is installed locally, write your own minimal wrapper (15-30 lines) rather than skipping. Example: @toon-format/toon was already in ~/.npm-global/lib/node_modules/ so a 14-line Node ESM wrapper at ~/.local/bin/toon was cleaner than installing the broken skill.
D4: Verify
skills_list | grep -i <name>
skill_view <name>
ls ~/.hermes/skills/<dir>/<slug>/
[ -x ~/.local/bin/<bin> ] && echo OK
D5: Worked example — installing TOON format
See references/clawhub-toon-example.md for the full evaluation matrix and install steps from the 2026-07-12 session (4 candidates evaluated, original recommendation @bonk-moltbot/toon was overturned after install verification: skill shipped without its promised scripts/toon wrapper — empty shell). The actual shipped artifact was a 14-line Node ESM wrapper at ~/.local/bin/toon that imports the locally-installed @toon-format/toon SDK directly. Lesson: never recommend an install path without ls scripts/ after clawhub install.
A1: 判断安装方法
如果用户给的仓库名遵循 owner/repo 格式（如 alchaincyf/nuwa-skill），先尝试 agentskills.io CLI：
npx skills add owner/repo
如果用户直接给了完整 URL，跳过此步，直接用 A2.
A1a: npx skills add 成功判定
- 输出包含
✔ Skill installed → 成功，跳到验证
- 输出
No valid skills found / Skills require a SKILL.md with name and description → 格式不兼容，走 A2
- 输出其他错误 → 检查网络，重试一次，不行走 A2
A2: git clone 回退方案（通用）
git clone --depth 1 https://github.com/<owner>/<repo> ~/.hermes/skills/openclaw-imports/<skill-name>
A2c: 批量 cp 模式（适用于大型仓库，子目录含多个独立 skill）
当仓库很大（数千文件）且技能散落在 skills/ 子目录中时，clone 到 ~/projects/（持久参考位置），用 cp -r 选择性安装到 Hermes skills 目录：
git clone --depth 1 https://github.com/<owner>/<repo> ~/projects/<repo>
mkdir -p ~/.hermes/skills/<category>/<skill-family>
for skill in skill-a skill-b skill-c; do
src="$HOME/projects/<repo>/skills/$skill"
[ -d "$src" ] && cp -r "$src" ~/.hermes/skills/<category>/<skill-family>/$skill
done
ls ~/.hermes/skills/<category>/<skill-family>/ | wc -l
使用 cp 而非 ln 的场景：
- 仓库不仅包含 skills，还有大量非技能资产（测试、CI、源文件）
- 只需要仓库中的一部分 skills
- 需要修改 SKILL.md 以适应 Hermes（如调整 frontmatter）
选择性复制技巧：先用 find ~/projects/<repo>/skills -name 'SKILL.md' | head -20 查看有哪些 skill，再根据用途筛选。
关键参数
--depth 1 — 浅克隆- 目标路径:
~/.hermes/skills/openclaw-imports/<skill-name>
- 超时处理：设置 120s+ 超时；如果中途被超时打断，先
rm -rf 再重试
- 网络限制：WSL 下若 git clone 超时，显式传递 proxy:
git -c http.proxy=http://127.0.0.1:7890 clone ...
A2b: 大规模多技能安装（子目录批量模式）
部分仓库（如 scientific-agent-skills）在一个 repo 内含 数百个技能，存放在 scientific-skills/、skills/ 等子目录中。直接 clone 到 ~/.hermes/skills/ 会混入非技能文件。正确做法：
-
克隆到持久化位置（而不是 ~/.hermes/skills/ 下）：
mv /tmp/<repo> ~/.hermes/<repo>
git clone --depth 1 https://github.com/<owner>/<repo> ~/.hermes/<repo>
-
批量创建软链接：遍历子目录下的每个技能目录，逐一链接到 ~/.hermes/skills/：
cd ~/.hermes/skills/
for dir in ~/.hermes/<repo>/<skills-subdir>/*/; do
name=$(basename "$dir")
[ ! -d "$name" ] && ln -s "$dir" "$name"
done
-
验证：
- 计数：
ls ~/.hermes/skills/ | wc -l — 确认总数合理增加
- 抽查：
skills_list 确认新技能出现在列表中
- 内容：
skill_view <任意-skill> 确认 SKILL.md 可读
-
注意 symlink 目标路径：使用绝对路径 ~/.hermes/... 而非相对路径，避免因目录变更导致断链。
技能名推断
优先使用 SKILL.md 中的 name: frontmatter，否则从 repo slug 推断。
A3: 验证注册状态
skills_list
skill_view <skill-name>
A4: 处理子目录技能
外部仓库可能将多个技能放在 examples/ 子目录中。Hermes 会自动发现这些子目录中的 SKILL.md 并注册为独立 skill — 无需额外操作。
Case B: Tool-with-Skill Install (Application Workflow)
For repos that are full AI applications with a skill interface (e.g., browser-use/video-use).
B1: 克隆到开发目录
Clone to ~/Developer/ (NOT directly into Hermes skills dir), because the tool has its own deps, venv, and scripts:
cd ~/Developer
git clone https://github.com/<owner>/<repo>.git
B2: 安装系统依赖
检查 install.md 或 README.md 了解系统依赖需求。常见的有：
| 依赖 | WSL Arch | macOS |
|---|
| ffmpeg/ffprobe | pacman -S ffmpeg | brew install ffmpeg |
| yt-dlp | pip install yt-dlp 或 uv pip install yt-dlp | brew install yt-dlp |
| Node.js | pacman -S nodejs npm | brew install node |
⚠️ 先检查是否已安装（command -v 而不是 which，在 WSL Arch 下 which 可能不存在）：
command -v ffmpeg && ffprobe -version | head -1
B3: 安装 Python 依赖
The tool likely has its own pyproject.toml:
cd ~/Developer/<repo>
uv sync
Note: If the tool's .venv conflicts with Hermes' active venv, that's fine — uv sync creates and uses its own .venv inside the repo.
B4: 配置 API Keys
Check if the tool needs API keys. Common key locations: .env.example → .env.
If a key is needed and not set, ask the user once:
"I need an <provider> API key for transcription / generation. Grab one at <url> and paste it here — I'll write it to ~/Developer/<repo>/.env. Or if you already have it exported, say 'use env'."
Key rules:
- Never echo the key back in tool output
- Never commit
.env
- After writing, sanity-check with a low-cost call (e.g., 200 response = key works)
B5: 注册为 Hermes Skill
两种链接模式，根据 SKILL.md 位置选择：
模式 1 — SKILL.md 在仓库根目录: symlink 整个仓库（helpers/、scripts/ 等相对 SKILL.md 解析）：
mkdir -p ~/.hermes/skills/<category>
ln -sfn ~/Developer/<repo> ~/.hermes/skills/<category>/<skill-name>
模式 2 — SKILL.md 在子目录（如 skills/<name>/SKILL.md）: 只 symlink 该子目录，不要链整个仓库（仓库根有 docs、examples、viewer 等非技能资产）：
mkdir -p ~/.hermes/skills/
ln -sf ~/Developer/<repo>/skills/<skill-name> ~/.hermes/skills/<skill-name>
判定方法: 查看仓库结构——ls <repo>/ 看根目录是否有 SKILL.md。如果没有，find <repo> -name SKILL.md -maxdepth 3 找到实际位置，按模式 2 处理。
Category choice rule of thumb:
productivity/ — most AI tools (video, image, editing)devops/ — deployment, monitoring toolscreative/ — art, animation tools
Skill name: Use the repo slug (e.g., video-use).
B6: 验证
skills_list
skill_view <skill-name>
ls ~/.hermes/skills/<category>/<skill-name>/helpers/
B7: 告知用户
告诉用户安装完成 + 下一步怎么做。格式示例：
video-use 已安装到 ~/Developer/video-use，已注册为 Hermes skill。
就缺 ElevenLabs API key 了——拿到后放到 .env 里就能用。
用法：把素材丢到文件夹，跑 Hermes 说"edit these into a launch video"即可。
Case C: npm-Package Skill Generator Install
For npm packages whose CLI generates SKILL.md files for other AI coding ecosystems (Claude Code, Cursor, OpenCode, etc.) and should be ported to Hermes.
User Preference
Many users prefer the native/original skill files over adapted versions — they want what the tool's ecosystem provides, not a reimplementation. Always install the original CLI and generate its skill files first, then copy/adapt for Hermes.
C1: Install the npm CLI
npm install -g @scope/package
Verify: package --version
C2: Generate Skill Files for Any Platform
Run the tool's init command in a temp directory to generate its skill files:
mkdir -p /tmp/<tool>-test && cd /tmp/<tool>-test
<tool> init --yes
Key things to verify:
- The tool supports many platforms (28+ in Comet's case). Pick one platform's output (e.g.,
.claude/skills/) as the source.
- Check what it generated:
find /tmp/<tool>-test -name 'SKILL.md'
- Check for companion scripts:
find /tmp/<tool>-test -name '*.sh'
C3: Identify Companion CLI Dependencies
Many skill generators depend on companion CLI tools that are also npm packages:
| Tool | Companion CLI | Install |
|---|
Comet (@rpamis/comet) | OpenSpec (@fission-ai/openspec) | npm install -g @fission-ai/openspec |
Initialize the companion tool too:
mkdir -p /tmp/<companion>-test && cd /tmp/<companion>-test
<companion> init --tools all --force
C4: Copy Skills to Hermes
Create a category directory under ~/.hermes/skills/ and copy all generated skills:
mkdir -p ~/.hermes/skills/<category>
for skill in /tmp/<tool>-test/.claude/skills/<tool>-*; do
name=$(basename "$skill")
cp -r "$skill" ~/.hermes/skills/<category>/"$name"
done
for skill in /tmp/<companion>-test/.claude/skills/<companion>-*; do
name=$(basename "$skill")
cp -r "$skill" ~/.hermes/skills/<category>/"$name"
done
for skill in /tmp/<tool>-test/.agents/skills/*; do
name=$(basename "$skill")
if [ ! -d ~/.hermes/skills/<target-category>/"$name" ] && [ ! -d ~/.hermes/skills/"$name" ]; then
cp -r "$skill" ~/.hermes/skills/<target-category>/"$name"
C5: Copy Companion Scripts
Tools like Comet include bash scripts for state management, guard checks, validation, and archiving:
cp /tmp/<tool>-test/.claude/skills/<tool>/scripts/*.sh ~/.hermes/skills/<category>/scripts/
C6: Fix Hermes-Specific Paths (Critical)
The generated SKILL.md files and scripts contain platform-specific path references (e.g., $HOME/.claude/skills/) that won't work in Hermes. You must patch them:
Common fixes needed:
- Search roots: Add
"$HOME/.hermes/skills/<category>" to bash script search roots
- Alternative find patterns: Add
-o -path '*/scripts/*.sh' alongside platform-specific paths
- Error messages: Update to reference Hermes paths
Example (Comet-specific):
COMET_SEARCH_ROOTS=( "." "$HOME/.hermes/skills/comet" "$HOME/.claude/skills" "$HOME/.codex/skills" "$HOME/.cursor/skills" )
COMET_GUARD=$(find ... -path '*/comet/scripts/comet-guard.sh' -o -path '*/scripts/comet-guard.sh')
C7: Verify Registration
hermes skills list 2>/dev/null | grep -i '<tool>'
skill_view <tool-or-skill-name>
C8: Clean Up Temp Files
rm -rf /tmp/<tool>-test /tmp/<companion>-test
C9: Save to Memory
Record the installation facts so future sessions know what's available.
Known Pitfalls
- Overlapping skills: The companion ecosystem may include skills that Hermes already has (e.g., Superpowers' subagent-driven-development, TDD, writing-plans). Check before copying to avoid conflicts.
- Script path resolution: Generated bash scripts often use hardcoded or narrow search roots. Always add Hermes' skills directory to the search paths and test with a dry run.
- CLI init fails: Some tools'
init commands are interactive-only and lack --yes/--force flags. In that case, manually create the test directory and inspect the npm package's bundled skill files directly under node_modules/.
which not available: WSL Arch may lack which. Use command -v for binary checks.
快速判断:这是"装 skill 的 skill"问题吗?
当用户问"有没有 X 市场的 skill" / "skill 市场" / "skill 商店"时,先查本 skill 是否覆盖 — 大概率就是这一个。常见来源对照:
| 用户说的 | 真实定位 | 装/查方式 |
|---|
| "Hermes skill 市场" / "https://hermes-agent.nousresearch.com/docs/zh-Hans/skills" | 本 skill 直接覆盖(12 个注册源、agentskills.io 索引) | npx skills add <owner/repo> 或 git clone |
| "AstrBot 插件市场" | 不是本 skill — 走 _archive/skill-finder-cn 或 AstrBot 原生 plugin marketplace | 别误推荐本 skill |
| "Claude Code / OpenCode / Cursor skills" | 同源,SKILL.md 格式通用,本 skill Case A 可装 | 直接装 |
| "Hermes 文档" (查/读) | 不需要 skill — hermes-agent umbrella + web_extract / browser_* 已经是答案 | 别造新 skill |
坑: _archive/skill-finder-cn 只覆盖 AstrBot 插件市场。看到"skill 市场"先想本 skill,别跳到 skill-finder-cn。
查 Hermes 文档的快捷方式
不需要额外 skill。hermes-agent umbrella + web_extract 已覆盖。.md 后缀 URL 走 web_extract 极快:
web_extract urls=["https://hermes-agent.nousresearch.com/docs/zh-Hans/skills"]
curl -s https://hermes-agent.nousresearch.com/docs/zh-Hans/<slug>.md
JS 重度页(Skills Hub 目录页)用 browser_console + document.body.innerText.slice(0, N) 拿分类目录,别死等 browser_snapshot 超时(30s 必挂)。
已知问题 (All Cases)
1. npx skills add 格式兼容性
npx skills add 底层使用 agentskills.io 的 SKILL.md parser，对 frontmatter 格式要求严格。即使 SKILL.md 包含 name: 和 description: 字段也可能失败。遇到此情况直接走 git clone 即可。
1b. npx skills add 交互式选择卡住
当仓库包含多个 skill 时，npx skills add 可能进入交互式选择界面（space to toggle → Enter to confirm），在非 PTY 终端下无法完成。现象：输出停在 Select skills to install 提示后不继续。此时直接走 A2 git clone 方案，不重试 npx。
2. 大仓库超时
大仓库（含 PNG/JPG/PDF）在 WSL 下 git clone 可能超时：
- 解决：
--depth 1 + 120s timeout
- 如果仍然超时:
curl -L https://api.github.com/repos/owner/repo/tarball | tar xz -C <target> --strip-components=1
3. 网络限制 (WSL)
WSL 下 GitHub/pypi 下载可能因代理问题不稳定：
-
command -v curl → curl -s --connect-timeout 5 https://github.com 检查连通性
-
如果 curl 通但 git 不通，显式传递代理:
git -c http.proxy=http://127.0.0.1:7890 -c https.proxy=http://127.0.0.1:7890 clone ...
-
如果还是超时 → 退化为 GitHub tarball 方式（见 #2）
-
AtomGit 国内镜像回退（GitHub 直连 + 代理均超时时使用）: 部分热门开源项目在 atomgit.com 有镜像。将 github.com/<owner>/<repo> 替换为 atomgit.com/<owner>/<repo>。示例：
git clone --depth 1 https://atomgit.com/hugohe3/ppt-master.git
⚠️ 不是所有项目都有镜像——先访问 https://atomgit.com/<owner>/<repo> 确认存在。
-
大文件 zip 下载不完整风险: GitHub archive zip 可能超过 500MB。curl 下载时若中途超时或被限速，文件大小不足且 unzip 报 End-of-central-directory signature not found。优先用 git clone（可续传），不用 curl + zip。
代理策略区分：git config vs 环境变量
| 目标 | 需要 | 示例 |
|---|
git clone | git config --global http.proxy 或 -c 参数 | git -c http.proxy=http://127.0.0.1:7890 clone ... |
pip install + httpx 下载 | HTTP_PROXY / HTTPS_PROXY 环境变量 | HTTP_PROXY=http://127.0.0.1:7890 pip install ... |
| Python 运行时 httpx 下载 | 同上，环境变量 | HTTP_PROXY=... python3 -c "from cloakbrowser import launch; ..." |
🚨 痛点案例: pip install cloakbrowser 成功（pip 走代理），但首次 launch() 触发 ~200MB Chromium 二进制下载时失败（httpx 不读 git config，需要 HTTP_PROXY 环境变量）。解决方案：启动前显式设环境变量。
HTTP_PROXY=http://127.0.0.1:7890 HTTPS_PROXY=http://127.0.0.1:7890 python3 -c "..."
4. Symlinked script paths in multi-platform repos
Some external skills (e.g., ui-ux-pro-max) use a multi-platform structure where the SKILL.md lives in .claude/skills/<name>/ but its referenced scripts and data live in src/<name>/scripts/. The .claude/ directory may contain symlinks to src/.
This means:
skill_view(name) → linked_files may report scripts at .claude/skills/<name>/scripts/- Trying to run from that path may fail or resolve differently
- The actual runnable scripts are at
src/<name>/scripts/
Fix: Before running scripts referenced by linked_files, locate them:
find ~/.hermes/skills/openclaw-imports/<repo> -name "search.py" -type f
Check each result; prefer the one under src/ (the canonical source) over .claude/ or cli/assets/.
5. WSL Arch: which 命令不可用
WSL Arch 的最小化安装可能没有 which 命令。始终使用 command -v 来检查可执行文件是否存在。
6. 追溯 skill 来源时，git remote -v 不可靠
陷阱: 技能目录下的 git remote -v 显示的是本地 workspace 跟踪仓库（如 publieople/hermes-workspace），不是技能的原始安装来源。skill 安装后，其目录可能被本地 workspace 的 git 覆盖，remote 会指向本地仓库而非源头。
正确做法: 追溯 skill 来源时，不要只看本地 git remote。优先级：
- 搜索 session 历史（
session_search）找安装记录——看当时用的 npx skills add、clawhub install 还是 git clone
- 检查
_archive/openclaw-imports/ 下的 DESCRIPTION.md 或安装时的会话上下文
- 在 ClawHub 搜索技能名（
clawhub search <name> 或网页 clawhub.ai）
- 比对已知公开仓库（
yfge/skill-finder、K-Dense-AI/scientific-agent-skills、openclaw/agent-skills 等）
常见案例: 本地 git remote 显示 publieople/hermes-workspace，但技能实际来自 clawhub install skill-vetter 或 npx skills add yfge/skill-finder。如果不区分，会把私有 workspace 链接误发给其他 agent 导致无法访问。
验证清单
每次安装完成后检查：
