BD 腾讯云资源管理工具
通过 tccli 命令行管理腾讯云资源。 Load when: 用户要查询云服务器、管理 Lighthouse、购买域名、配置 DNS、 检查安全组、做安全巡检、部署应用、挂载云硬盘、部署 OpenClaw、 监控资源状态、SSL 证书检查、CAM 权限管理。 Covers: CVM、Lighthouse、CBS、VPC、DNSPod、SSL、CAM、Monitor、TAT、Domain。 Use for: "帮我看看服务器"、"查下域名到期没"、"安全检查"、"部署应用"、 "买个云硬盘"、"建个网站"、"查下证书"、"检查安全组"、"创建实例"、"退出登录"、"切换账号"。 Biases towards: tccli 命令行操作，查询优先于修改，确认后再执行， 优先通过 tccli --help 获取最新参数而非依赖预训练知识。
As a process D 39/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
What is at stake
The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.
The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.
Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.
How to improve
- Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 4
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high Dangerous commands
cmd-pipe-to-shellreferences/lighthouse-app-deploy.md:235Downloads and executes remote code from an unrecognised host (pipe to shell)curl -fsSL https://get.docker.com | sh
Medium and low: 3
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medium Dangerous commands
cmd-pipe-to-shell-known-hostreferences/lighthouse-app-deploy.md:272Pipe-to-shell installer from a well-known host (still executes remote code)curl -fsSL https://deb.nodesource.com/setup_20.x | bash -
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low Dangerous commands
cmd-background-processreferences/lighthouse-app-deploy.md:236Starts a background / autostarted processsystemctl enable docker && systemctl start docker
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low Dangerous commands
cmd-background-processreferences/lighthouse-app-deploy.md:346Starts a background / autostarted processsystemctl enable app
Files scanned: 10. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
name-formatname should be kebab-case (lowercase letters, digits, hyphens)
Process rating: all ten parameters 39/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 6 mutating operations with no state check
- 40Consistency. Frontmatter name (腾讯云资源管理工具) differs from the folder (tencentcloud-management-tool)
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 100Steps. 15 steps
- 100Execution cost. Instruction body is 2659 tokens
- low 11 top-level sections: this looks like several domains in one skill
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- -229 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +5Description quotes 2 example trigger phrases
- +3Description length 371: enough signal without eating the budget
- +4Structure: 25 headings
- +3Step-by-step instructions: 15 items
- +4Has examples (26 code blocks)
- +4Reference files are cited in the instructions (7 of 7)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 89.