Hy 3D Gen
kangarooking/kangarooking-skills
输入文字或图片,通过腾讯混元生3D TokenHub/OpenAI 兼容接口或腾讯云 SDK 生成3D模型。支持文生3D、图生3D、多视图生3D、PBR、白模、草图生3D、智能拓扑生3D;当用户要求生成或查询混元3D模型时使用。
腾讯云智能顾问助手 — 通过 AK/SK 鉴权调用腾讯云智能顾问 API,管理云架构图(查询目录、获取架构列表和详情、获取架构评估结果)及风险评估(查询评估项、按产品/分组/风险等级筛选)。当用户要求查看云架构、查询架构目录、获取架构详情、查看架构评估结果、查看风险评估项、巡检项、云资源风险等智能顾问相关操作时使用。
$ npx skills add LeoYeAI/openclaw-master-skills --skill tencent-cloudq -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills tencent-cloudq --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/tsa-cloudq .claude/skills/tencent-cloudq && 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 "tencent-cloudq" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/tsa-cloudq into .claude/skills/tencent-cloudq/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tencent-cloudq", 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/tsa-cloudqType 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 tencent-cloudq -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills tencent-cloudq --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/tsa-cloudq .agents/skills/tencent-cloudq && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "tencent-cloudq" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/tsa-cloudq into .agents/skills/tencent-cloudq/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tencent-cloudq", 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 tencent-cloudq -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills tencent-cloudq --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/tsa-cloudq .cursor/skills/tencent-cloudq && 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 "tencent-cloudq" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/tsa-cloudq into .cursor/skills/tencent-cloudq/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tencent-cloudq", 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/tsa-cloudq--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 tencent-cloudq -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills tencent-cloudq --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/tsa-cloudq .gemini/skills/tencent-cloudq && 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 "tencent-cloudq" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/tsa-cloudq into .gemini/skills/tencent-cloudq/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tencent-cloudq", 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 tencent-cloudqInstalls 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 tencent-cloudq -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/tsa-cloudq .github/skills/tencent-cloudq && 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 "tencent-cloudq" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/tsa-cloudq into .github/skills/tencent-cloudq/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tencent-cloudq", 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 tencent-cloudq -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 tencent-cloudq --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/tsa-cloudq .opencode/skills/tencent-cloudq && 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 "tencent-cloudq" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/tsa-cloudq into .opencode/skills/tencent-cloudq/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tencent-cloudq", 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.
tencent-cloudq腾讯云智能顾问助手 — 通过 AK/SK 鉴权调用腾讯云智能顾问 API,管理云架构图(查询目录、获取架构列表和详情、获取架构评估结果)及风险评估(查询评估项、按产品/分组/风险等级筛选)。当用户要求查看云架构、查询架构目录、获取架构详情、查看架构评估结果、查看风险评估项、巡检项、云资源风险等智能顾问相关操作时使用。
Tencent Cloudq is an agent skill from LeoYeAI/openclaw-master-skills. 腾讯云智能顾问助手 — 通过 AK/SK 鉴权调用腾讯云智能顾问 API,管理云架构图(查询目录、获取架构列表和详情、获取架构评估结果)及风险评估(查询评估项、按产品/分组/风险等级筛选)。当用户要求查看云架构、查询架构目录、获取架构详情、查看架构评估结果、查看风险评估项、巡检项、云资源风险等智能顾问相关操作时使用。
Its SKILL.md is about 3.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 15 other files, including scripts and reference files (for example `_meta.json`, `check_env.py` and `references/DescribeArch.md`).
It works with Tencent Cloud and Python. The repository describes itself as: 🧠 Curated collection of 1209+ best OpenClaw skills — weekly updated by MyClaw.ai. The licence is MIT.
4 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit e5199b5. It shows what the files ask for, not the result of running them.
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.
Ships 5 files in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
python3From the folder's file list and the shell code blocks in SKILL.md.
Hosts in commands or code, which the agent is likely to contact:
console.cloud.tencent.comcloud.tencent.comFrom URLs in SKILL.md, links to its own repository left out.
Names these keys or tokens, usually read from environment variables:
TENCENTCLOUD_SECRET_KEYTENCENTCLOUD_TOKENSECRET_KEYFrom names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Tencent Cloudq loads about 3.7k tokens when it runs, and up to ~7.6k if it reads all its reference files. Until then it costs about 44 tokens; SKILL.md has 690 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.
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.
The full file from LeoYeAI/openclaw-master-skills at commit e5199b5, republished under its MIT licence (© LeoYeAI). 690 words, ~3,739 tokens.
.claude/skills/tencent-cloudq/SKILL.md (or your agent's skills folder). This skill also uses 13 other files; get the full folder from GitHub.核心能力:通过 AK/SK 鉴权调用腾讯云智能顾问(Tencent Cloud Smart Advisor)API,管理云架构图的目录与详情、获取架构评估结果,以及查询风险评估项。
使用腾讯云 API AK/SK 签名认证(TC3-HMAC-SHA256),通过环境变量配置密钥:
TENCENTCLOUD_SECRET_ID — 腾讯云 SecretId(必填)TENCENTCLOUD_SECRET_KEY — 腾讯云 SecretKey(必填)密钥获取地址:https://console.cloud.tencent.com/cam/capi
环境变量必须永久写入 shell 配置文件,确保新会话中仍然生效:
Linux / macOS(写入 ~/.bashrc 或 ~/.zshrc):
echo 'export TENCENTCLOUD_SECRET_ID="your-secret-id"' >> ~/.bashrc
echo 'export TENCENTCLOUD_SECRET_KEY="your-secret-key"' >> ~/.bashrc
source ~/.bashrcWindows PowerShell(写入用户级环境变量):
[Environment]::SetEnvironmentVariable("TENCENTCLOUD_SECRET_ID", "your-secret-id", "User")
[Environment]::SetEnvironmentVariable("TENCENTCLOUD_SECRET_KEY", "your-secret-key", "User")为生成控制台免密登录链接,需要配置 CAM 角色。角色配置分为 检测 和 创建 两个独立步骤,角色创建属于 IAM 写入操作,必须在用户明确同意后才能执行。
运行环境自检脚本,检测依赖、版本更新、密钥、角色配置状态:
python3 {baseDir}/check_env.py自检脚本 仅做只读检测,不会创建或修改任何资源。返回码含义:
0 = 环境就绪(密钥 + 角色全部正常)1 = Python 版本不满足要求2 = AK/SK 未配置或无效3 = 角色未配置(需要执行步骤二)4 = Skill 版本过旧,请更新 Skill脚本首次运行时会自动检查本地 _meta.json 中的版本号与远端最新版本是否一致,若发现新版本则提示更新并退出(返回码 4)。可通过 --skip-update 参数跳过版本检查。
当 check_env.py 返回码为 3(角色未配置)时,必须向用户展示角色创建方案并等待同意:
向用户说明以下内容:
advisor,仅用于免密登录控制台查看智能顾问信息QcloudAdvisorFullAccess(智能顾问只读访问权限,不影响其他云资源)用户同意后,执行角色创建脚本:
python3 {baseDir}/scripts/create_role.py脚本输出 JSON 格式结果,success: true 表示创建成功并已保存配置。
用户拒绝时,提供手动配置方式(方式二、三、四)。
运行配置向导,从已有角色中选择,或交互式创建新角色:
python3 {baseDir}/scripts/setup_role.py只需提供角色名称,系统自动获取账号 UIN。将以下内容写入 shell 配置文件(如 ~/.bashrc 或 ~/.zshrc):
echo 'export TENCENTCLOUD_ROLE_NAME="advisor"' >> ~/.bashrc
source ~/.bashrc系统会自动调用 API 获取您的账号 UIN,并拼接完整的 roleArn。
手动设置完整的角色 ARN,写入 shell 配置文件(如 ~/.bashrc 或 ~/.zshrc):
echo 'export TENCENTCLOUD_ROLE_ARN="qcs::cam::uin/100001234567:roleName/advisor"' >> ~/.bashrc
source ~/.bashrcTENCENTCLOUD_TOKEN — 临时密钥 Token(使用临时密钥时设置)TENCENTCLOUD_ROLE_SESSION — 角色会话名称(默认 advisor-session)TENCENTCLOUD_STS_DURATION — 临时凭证有效期秒数(默认 3600,即 1 小时;最大 43200,即 12 小时)注意:所有环境变量均需永久写入 shell 配置文件(如
~/.bashrc、~/.zshrc),export仅对当前会话生效,新开会话会丢失。
系统按以下优先级加载角色配置:
TENCENTCLOUD_ROLE_ARN(完整 ARN)~/.tencent-cloudq/config.jsonTENCENTCLOUD_ROLE_NAME + 自动获取账号 UIN每次操作前必须先执行环境检测。初始化分为 版本检查、环境检测 和 角色创建 三个阶段,角色创建属于 IAM 写入操作,必须在用户明确同意后才能执行。
第一步:运行环境检测
python3 {baseDir}/check_env.py脚本会依次执行以下检测:
_meta.json 版本,与远端最新版本对比)根据返回码判断状态:
0 = 环境就绪,可以正常使用所有功能1 = Python 版本不满足要求 → 提示用户升级 Python2 = AK/SK 未配置或无效 → 提示用户配置密钥3 = 角色未配置 → 执行第二步4 = Skill 版本过旧 → 提示用户更新 Skill版本检查说明:脚本首次运行时会自动对比本地版本与远端版本。若远端有新版本,脚本会输出当前版本和最新版本号,并以返回码 4 退出。网络不可用或远端接口异常时,版本检查会被跳过,不影响后续检测。可通过 --skip-update 参数主动跳过版本检查。
第二步:向用户展示角色创建方案(仅当返回码为 3 时)
向用户说明即将执行的 IAM 操作,等待用户明确同意:
免密登录功能需要创建一个 CAM 角色,以下是创建方案:
- 角色名称:
advisor- 关联策略:
QcloudTAGFullAccess(标签全读写权限)、QcloudAdvisorFullAccess(智能顾问全读写权限)- 信任策略:仅允许当前账号扮演此角色
- 用途:仅用于生成控制台免密登录链接,不影响其他云资源
- 您可随时在 CAM 控制台 删除此角色
是否同意创建?
第三步:执行角色创建(仅在用户同意后)
python3 {baseDir}/scripts/create_role.py脚本输出 JSON 格式结果,success: true 表示创建成功。
第四步:再次运行环境检测,确认环境就绪
python3 {baseDir}/check_env.py返回码 0 表示初始化完成,所有功能可用。
python3 {baseDir}/check_env.py --quiet静默模式下仅输出错误信息,适合其他脚本调用获取环境状态。角色未配置时返回码 3,不会自动创建角色。
python3 {baseDir}/check_env.py --skip-update跳过远端版本对比,直接进行后续环境检测。适用于离线环境或已知无需更新的场景。可与 --quiet 组合使用。
所有接口通过统一的签名脚本调用,服务固定参数:
advisoradvisor.tencentcloudapi.com2020-07-21python3 {baseDir}/scripts/tcloud_api.py advisor advisor.tencentcloudapi.com <Action> 2020-07-21 '<payload>' [region]所有接口频率限制均为 20 次/秒。使用某个接口前,必须先加载对应的接口文档获取参数、返回值和展示规则等详细信息。
获取指定云架构图的详细信息。必填参数:ArchId、Username。
{baseDir}/references/DescribeArch.mdpython3 {baseDir}/scripts/tcloud_api.py advisor advisor.tencentcloudapi.com DescribeArch 2020-07-21 '{"ArchId":"arch-xxx","Username":"user1"}'分页获取云架构图列表,支持按名称、关键词、文件夹等筛选。必填参数:PageNumber、PageSize。
{baseDir}/references/DescribeArchList.mdpython3 {baseDir}/scripts/tcloud_api.py advisor advisor.tencentcloudapi.com DescribeArchList 2020-07-21 '{"PageNumber":1,"PageSize":10}'查询云架构图的目录树结构。无必填参数。
{baseDir}/references/ListDirectoryV2.mdpython3 {baseDir}/scripts/tcloud_api.py advisor advisor.tencentcloudapi.com ListDirectoryV2 2020-07-21 '{}'查询新版目录下的待整理(未归类)目录结构。无必填参数。
{baseDir}/references/ListUnorganizedDirectory.mdpython3 {baseDir}/scripts/tcloud_api.py advisor advisor.tencentcloudapi.com ListUnorganizedDirectory 2020-07-21 '{}'查询全量风险评估项(巡检项),支持客户端按产品/分组/风险等级筛选。无必填参数。
{baseDir}/references/DescribeStrategies.mdpython3 {baseDir}/scripts/tcloud_api.py advisor advisor.tencentcloudapi.com DescribeStrategies 2020-07-21 '{}'获取指定架构图的 Well-Architected 评估结果,含总分、各维度得分和治理建议。必填参数:ArchId。
{baseDir}/references/DescribeLastEvaluation.mdpython3 {baseDir}/scripts/tcloud_api.py advisor advisor.tencentcloudapi.com DescribeLastEvaluation 2020-07-21 '{"ArchId":"arch-xxx"}'当接口返回结果中包含架构图(含 ArchId 字段)时,必须调用免密登录脚本为用户生成腾讯云控制台直达链接,用户点击即可免登录跳转到对应页面。架构图列表场景下,只需为第一张架构图生成免密链接。
⚠️ 重要:免密登录链接每次都必须重新生成,不可缓存或复用之前生成的链接。每次向用户展示时,都必须重新调用
login_url.py生成新的链接。
为生成免密登录链接,需要先完成角色配置。请按「二、前置检查」中的初始化工作流完成角色配置(检测 → 用户同意 → 创建角色 → 确认就绪)。
也可以通过以下方式手动配置角色:
配置向导
python3 {baseDir}/scripts/setup_role.py简化配置(写入 ~/.bashrc 或 ~/.zshrc)
echo 'export TENCENTCLOUD_ROLE_NAME="advisor"' >> ~/.bashrc && source ~/.bashrc完整配置(写入 ~/.bashrc 或 ~/.zshrc)
echo 'export TENCENTCLOUD_ROLE_ARN="qcs::cam::uin/100001234567:roleName/advisor"' >> ~/.bashrc && source ~/.bashrc可选环境变量:
TENCENTCLOUD_ROLE_SESSION — 角色会话名称(默认 advisor-session)TENCENTCLOUD_STS_DURATION — 临时凭证有效期秒数(默认 3600,即 1 小时;最大 43200,即 12 小时)提示: 详细配置说明请参考"一、鉴权方式"章节
python3 {baseDir}/scripts/login_url.py "<目标页面URL>"架构图控制台页面 URL 格式:https://console.cloud.tencent.com/advisor?archId={ArchId}
# 为指定架构图生成免密链接
python3 {baseDir}/scripts/login_url.py \
"https://console.cloud.tencent.com/advisor?archId=arch-gvqocc25"
# 跳转到智能顾问首页
python3 {baseDir}/scripts/login_url.py \
"https://console.cloud.tencent.com/advisor"{
"success": true,
"action": "GenerateLoginURL",
"data": {
"loginUrl": "https://cloud.tencent.com/login/roleAccessCallback?algorithm=sha256&secretId=...&token=...&signature=...&s_url=https%3A%2F%2Fconsole.cloud.tencent.com%2Fadvisor%3FarchId%3Darch-gvqocc25",
"targetUrl": "https://console.cloud.tencent.com/advisor?archId=arch-gvqocc25",
"expireSeconds": 3600
},
"requestId": "xxx"
}| 字段 | 说明 |
|---|---|
loginUrl | 免密登录完整 URL,用户点击可直接跳转控制台 |
targetUrl | 登录后跳转的目标页面 |
expireSeconds | 链接有效期(秒) |
免密登录 URL 非常长,严禁直接展示完整 URL。每次展示时必须重新调用脚本生成新链接(链接不可复用),并以 Markdown 超链接格式展示:
[跳转控制台](免密登录URL)示例输出:
架构图名称:生产环境架构
架构图 ID:arch-gvqocc25
[跳转控制台](https://cloud.tencent.com/login/roleAccessCallback?algorithm=sha256&secretId=...&token=...&signature=...&s_url=https%3A%2F%2Fconsole.cloud.tencent.com%2Fadvisor%3FarchId%3Darch-gvqocc25)列表场景示例(仅第一张架构图附带免密链接):
1. 生产环境架构(arch-abc123)— [跳转控制台](免密登录URL)
2. 测试环境架构(arch-def456)
3. 预发布环境架构(arch-ghi789)当用户查询架构图时,完整流程如下:
# 第一步:查询架构列表
RESULT=$(python3 {baseDir}/scripts/tcloud_api.py \
advisor advisor.tencentcloudapi.com \
DescribeArchList 2020-07-21 \
'{"PageNumber":1,"PageSize":10}')
# 第二步:从结果中提取 ArchId(假设取第一个)
ARCH_ID=$(echo "$RESULT" | python3 -c "
import sys, json
data = json.load(sys.stdin)
arch_list = data.get('data', {}).get('ArchList', [])
if arch_list:
print(arch_list[0]['ArchId'])
")
# 第三步:为该架构图生成免密登录链接
LOGIN_RESULT=$(python3 {baseDir}/scripts/login_url.py \
"https://console.cloud.tencent.com/advisor?archId=${ARCH_ID}")
# 第四步:提取 loginUrl 并以超链接形式展示
LOGIN_URL=$(echo "$LOGIN_RESULT" | python3 -c "
import sys, json
data = json.load(sys.stdin)
print(data.get('data', {}).get('loginUrl', ''))
")
# 输出给用户(Markdown 超链接格式,注意:每次都必须重新生成链接)
echo "[跳转控制台](${LOGIN_URL})"所有接口调用的输出均为统一的 JSON 格式,通过 success 字段区分成功与失败。
{
"success": true,
"action": "DescribeArchList",
"data": { ... },
"requestId": "9cbe807c-..."
}| 字段 | 类型 | 说明 |
|---|---|---|
success | Boolean | 固定为 true |
action | String | 调用的接口名称 |
data | Object | 接口返回的业务数据(已去除 RequestId) |
requestId | String | 腾讯云请求 ID,用于问题排查 |
{
"success": false,
"action": "DescribeArchList",
"error": {
"code": "AuthFailure.SecretIdNotFound",
"message": "The SecretId is not found, please ensure that your SecretId is correct."
},
"requestId": "ed93f3cb-..."
}| 字段 | 类型 | 说明 |
|---|---|---|
success | Boolean | 固定为 false |
action | String | 调用的接口名称 |
error.code | String | 错误码 |
error.message | String | 错误描述 |
requestId | String | 腾讯云请求 ID(网络错误时为空) |
| 错误码 | 含义 |
|---|---|
MissingParameter | 脚本调用缺少必要参数 |
MissingCredentials | 未配置 AK/SK 环境变量 |
NetworkError | 网络请求失败,无法连接 API |
ParseError | 响应不是有效的 JSON |
| 错误码 | 含义 | 解决方案 |
|---|---|---|
AuthFailure.SecretIdNotFound | SecretId 不存在 | 检查 TENCENTCLOUD_SECRET_ID |
AuthFailure.SignatureFailure | 签名错误 | 检查 TENCENTCLOUD_SECRET_KEY |
AuthFailure.SignatureExpire | 签名过期 | 检查本地时间是否准确 |
AuthFailure.TokenFailure | Token 错误 | 检查 TENCENTCLOUD_TOKEN |
AuthFailure.UnauthorizedOperation | 未授权 | 检查 CAM 策略 |
ResourceNotFound | 资源不存在 | 检查 ArchId 等参数是否正确 |
InvalidParameter | 参数错误 | 检查请求参数格式和类型 |
InvalidParameterValue | 参数取值错误 | 检查参数值范围 |
RequestLimitExceeded | 频率限制 | 降低调用频率(限 20 次/秒) |
QcloudTAGFullAccess 和 QcloudAdvisorFullAccess 策略TENCENTCLOUD_TOKENap-guangzhou,Region 为可选参数TENCENTCLOUD_STS_DURATION 调整(最大 43200 秒,即 12 小时)[跳转控制台](免密登录URL) 超链接形式展示,严禁直接展示完整 URL。每次展示都必须重新调用 login_url.py 生成新链接,不可缓存或复用之前生成的链接https://console.cloud.tencent.com/advisor/assess?strategyName={URL编码后的Name}read_file 加载 {baseDir}/references/<Action>.md 获取完整的参数说明、返回字段、展示格式等详细信息本 Skill 需要以下环境变量才能正常运行:
| 环境变量 | 必填 | 说明 |
|---|---|---|
TENCENTCLOUD_SECRET_ID | 是 | 腾讯云 API SecretId |
TENCENTCLOUD_SECRET_KEY | 是 | 腾讯云 API SecretKey |
密钥仅通过环境变量读取,不会被写入文件、日志或网络传输中。
本 Skill 包含以下 CAM(访问管理)操作。写入类操作仅由独立脚本 scripts/create_role.py 执行,且必须在用户明确同意后才会运行。check_env.py 仅执行只读检测操作。
| API 操作 | 类型 | 所在脚本 | 说明 |
|---|---|---|---|
sts:GetCallerIdentity | 只读 | check_env.py / create_role.py | 获取当前账号 UIN |
cam:GetRole | 只读 | check_env.py / create_role.py | 检查角色是否存在 |
cam:DescribeRoleList | 只读 | setup_role.py | 列出可用角色供用户选择 |
cam:CreateRole | 写入 | scripts/create_role.py | 创建 advisor 角色(需用户明确同意后执行) |
cam:AttachRolePolicy | 写入 | scripts/create_role.py | 关联 QcloudAdvisorFullAccess 策略(随角色创建执行) |
sts:AssumeRole | 敏感 | login_url.py | 扮演角色获取临时凭证(用于生成免密登录链接) |
cam:DeleteRole | 写入 | scripts/cleanup.py | 删除 advisor 角色(仅 --cloud 模式,需用户明确确认) |
~/.tencent-cloudq/config.json 仅保存角色 ARN 和账号 UIN,不保存任何密钥700,配置文件设为 600,仅当前用户可读写*.tencentcloudapi.com)和登录域名(cloud.tencent.com)用户可随时运行清理脚本删除本机上的所有配置和缓存:
# 交互式清理(逐项确认)
python3 {baseDir}/scripts/cleanup.py
# 一键清理所有本地配置
python3 {baseDir}/scripts/cleanup.py --all
# 一键清理所有本地配置 + 云端 advisor 角色
python3 {baseDir}/scripts/cleanup.py --all --cloud清理范围:
~/.tencent-cloudq/(含 config.json){系统临时目录}/.tcloud_advisor_uin_cacheTENCENTCLOUD_* 系列(SECRET_ID、SECRET_KEY、TOKEN、ROLE_ARN、ROLE_NAME、ROLE_SESSION、STS_DURATION),脚本会自动检测已设置的变量并生成对应平台的清理命令(source 脚本 / PowerShell 脚本)advisor(仅 --cloud 模式,需配置 AK/SK)© LeoYeAI, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 13 other files (scripts, references) in skills/tsa-cloudq of LeoYeAI/openclaw-master-skills.
Open the folder on GitHubat commit e5199b5
Tencent Cloudq 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 |
|---|---|---|---|---|---|---|
| Tencent Cloudq this skillLeoYeAI/openclaw-master-skills | 2.2k | — | ~3.7k | Automated safety check: Pass | MIT | |
| Hy 3D Genkangarooking/kangarooking-skills | 661 | — | ~2.4k | Automated safety check: Notes | None | |
| Tencentcloud OCRinfometa/workbuddyskills | 346 | — | ~1.1k | Automated safety check: Pass | None | |
| MCP Server Builderanthropics/skills | 180k | 63 repos | ~2.3k | Automated safety check: Pass | Apache-2.0 | |
| PDF Processinganthropics/skills | 180k | 48 repos | ~2k | Automated safety check: Pass | Proprietary | |
| NotebookLM Research AssistantPleasePrompto/notebooklm-skill | 7.8k | 14 repos | ~2.4k | Automated safety check: Notes | MIT |
kangarooking/kangarooking-skills
输入文字或图片,通过腾讯混元生3D TokenHub/OpenAI 兼容接口或腾讯云 SDK 生成3D模型。支持文生3D、图生3D、多视图生3D、PBR、白模、草图生3D、智能拓扑生3D;当用户要求生成或查询混元3D模型时使用。
infometa/workbuddyskills
腾讯云通用文字识别(高精度版)(GeneralAccurateOCR) 技能包。当用户发送/粘贴图片、提供图片URL、或要求识别图片中的文字时,应自动调用此技能。支持图像整体文字的检测和识别,支持中文、英文、中英文、数字和特殊字符号的识别,并返回文字框位置和文字内容。适用于文字较多、版式复杂、对识别准召率要求较高的场景,如网络图片、街景店招牌、法律卷宗、多语种简历等场景。支持图片Base64和U…
anthropics/skills
Guides the design and implementation of Model Context Protocol servers in TypeScript or Python, from tool naming and error messages to evaluation.
anthropics/skills
Handles everyday PDF jobs in Python and on the command line: extract text and tables, merge, split, rotate, watermark, fill forms, encrypt and OCR.
PleasePrompto/notebooklm-skill
Lets Claude Code ask questions of your Google NotebookLM notebooks through browser automation and return answers grounded in your uploaded sources.
browser-use/video-use
Produces math and technical explainer videos with Manim Community Edition: concept animations, equation derivations, algorithm walkthroughs and data stories.
LeoYeAI/openclaw-master-skills
Manages pipelines on a DevOps quality and efficiency platform through its OpenAPI: list workspaces and templates, create, update, run and cancel pipelines, and read run records.
LeoYeAI/openclaw-master-skills
Patches OpenClaw's Feishu extension so an edited document triggers an isolated agent session that reads the doc and replies inline, turning it into a live chat space.
LeoYeAI/openclaw-master-skills
Multi-context memory management system for OpenClaw agents with group-isolated storage, global shared memory, workspace organization, and group-specific skills isolation.
LeoYeAI/openclaw-master-skills
Runs a brand's AI-search visibility work end to end: diagnosing how AI platforms represent it, repositioning it, producing AI-optimized content and monitoring ongoing mentions.
LeoYeAI/openclaw-master-skills
Installs and authenticates the gws CLI, then automates Gmail, Drive, Sheets, Calendar, Docs, Chat and Tasks with ready-made recipes, persona bundles and security audits.
LeoYeAI/openclaw-master-skills
Runs four advisor roles, a fitness coach, nutritionist, data analyst and TCM practitioner, to build a health profile and track workouts, diet and wellness over time.
Works with
腾讯云智能顾问助手 — 通过 AK/SK 鉴权调用腾讯云智能顾问 API,管理云架构图(查询目录、获取架构列表和详情、获取架构评估结果)及风险评估(查询评估项、按产品/分组/风险等级筛选)。当用户要求查看云架构、查询架构目录、获取架构详情、查看架构评估结果、查看风险评估项、巡检项、云资源风险等智能顾问相关操作时使用。. Tencent Cloudq is an agent skill from LeoYeAI/openclaw-master-skills.
Run `npx skills add LeoYeAI/openclaw-master-skills --skill tencent-cloudq -a claude-code`. Or copy the skill folder (skills/tsa-cloudq in LeoYeAI/openclaw-master-skills) into .claude/skills/tencent-cloudq in your project. Claude Code loads it when a task matches its description.
Run `npx skills add LeoYeAI/openclaw-master-skills --skill tencent-cloudq -a codex`. Or copy the skill folder (skills/tsa-cloudq in LeoYeAI/openclaw-master-skills) into .agents/skills/tencent-cloudq in your project. Codex loads it when a task matches its description.
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 tencent-cloudq -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/tencent-cloudq, .gemini/skills/tencent-cloudq, .github/skills/tencent-cloudq and .opencode/skills/tencent-cloudq in your project.
Going by SKILL.md and its folder, Tencent Cloudq needs Python for the scripts in its folder, the command-line tools its instructions call (python3) and credentials named TENCENTCLOUD_SECRET_KEY, TENCENTCLOUD_TOKEN and SECRET_KEY. Our summary lists: Python 3; A credential in TENCENTCLOUD_SECRET_KEY; A credential in TENCENTCLOUD_TOKEN.
SKILL.md names 2 domains. In commands or code: console.cloud.tencent.com and cloud.tencent.com; the agent is likely to contact these when it follows the instructions. This is read from the text; nothing was executed.
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.
Tencent Cloudq is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 3.7k tokens (SKILL.md is roughly 15k 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 3.9k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Tencent Cloudq: Hy 3D Gen (kangarooking/kangarooking-skills, 661 stars), Tencentcloud OCR (infometa/workbuddyskills, 346 stars), MCP Server Builder (anthropics/skills, 180k stars) and PDF Processing (anthropics/skills, 180k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
LeoYeAI (a GitHub user) maintains it in LeoYeAI/openclaw-master-skills, which has 2,160 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.