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腾讯云 AndonQ 腾讯云技术服务专家 — 不切窗口、不排队，即刻获得腾讯云全产品线专业解答。支持工单查询（列表/详情/流水）、创建工单（自动匹配产品分类）、集团工单与需求单管理、腾讯云全产品线智能问答，以及通过 tccli 调用腾讯云任意云 API（如 CVM、CBS、CAM 等）。当用户查询工单、查看工单详情、创建工单、咨询腾讯云产品问题（如 CVM、轻量应用服务器、COS 等）、查询集团工单/需求单、要求找人工客服、或需要调用腾讯云 API 进行资源管理操作时使用。

LeoYeAI/openclaw-master-skills Agent Skills author: LeoYeAI MIT 18 files body ≈ 4 125 tokens Open the sourcegithub.com↗ analyzed 2 d ago

腾讯云 AndonQ 腾讯云技术服务专家 — 不切窗口、不排队，即刻获得腾讯云全产品线专业解答。支持工单查询（列表/详情/流水）、创建工单（自动匹配产品分类）、集团工单与需求单管理、腾讯云全产品线智能问答，以及通过 tccli 调用腾讯云任意云 API（如 CVM、CBS、CAM…

As a process D 42/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationAI and agentstype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
B
81/100
safety, quality, tests
Safety 60%
90
Quality 40%
68
Run on models
none yet
Process rating
D
42/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Dangerous commands medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

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.

For the author

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

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
For the model run — optional
  • 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 · 2

✓ No critical or high findings

Medium and low: 2
  • medium Dangerous commands cmd-shell-rc SKILL.md:41
    Writes to a shell startup file
    echo 'export TENCENTCLOUD_SECRET_ID="your-secret-id"' >> ~/.zshrc
  • medium Dangerous commands cmd-shell-rc SKILL.md:42
    Writes to a shell startup file
    echo 'export TENCENTCLOUD_SECRET_KEY="your-secret-key"' >> ~/.zshrc

Files scanned: 18. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 42/100

  • 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. 3 mutating operations with no state check
  • 60Tools and files. Uses tools (bash, web, python) that frontmatter does not declare
  • 70Execution cost. Instruction body is 4125 tokens
  • 100Steps. 101 steps
  • 100Consistency. Name and required fields are in place
  • low The response is described with custom markup (5 tags): a typed call is more reliable

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

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • -33 of 5 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 239: enough signal without eating the budget
  • +4Structure: 55 headings
  • +3Step-by-step instructions: 101 items
  • +4Has examples (36 code blocks)
  • +4Reference files are cited in the instructions (10 of 10)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 68.