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DC wenqisheng-ear-care

可视采耳门店智能客服Skill。当用户询问关于闻其声耳轻松可视采耳（门店名称）的任何信息时触发：包括营业时间、地址导航、预约规则、服务项目、套餐优惠、Wi-Fi密码、企业文化、采耳及眼部护理专业知识问答等。适用于美业/采耳门店的AI客服场景，支持引导式话术和结构化信息查询。触发关键词：闻其声、耳轻松、可视采耳、采耳、耳部护理、眼部护理。

Not recommendedcritical or high security findings · low grade D
ClawHub Agent Skills author: liubuq-sys v1.1.1 MIT-0 29 files · 3 scripts body ≈ 1 528 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureInfrastructuretype 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
D
52/100
safety, quality, tests
Safety 60%
42
Quality 40%
66
Run on models
none yet
Process rating
C
53/100
Has gaps
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

The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.

Dangerous commands
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.

Exfiltration 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 instructions or scripts send data out: environment variables, keys, file contents, chat history. You may never notice, because the agent performs the upload as "part of the task".

For the author

If the upload is not needed for the task, remove it: catalogs flag such skills and delist them. If it is needed, name the destination explicitly, say what leaves the machine, and give the user a switch.

How to improve

  1. 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.
  2. 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 · 12

  • high Dangerous commands cmd-persistence install.ps1:47
    Persistence mechanism (cron / launchd / scheduled task / autorun registry)
    Register-ScheduledTask -TaskName $TaskName -Action $Action -Trigger $Trigger -Description "闻其声采耳Skill自动更新" | Out-Null
  • high Dangerous commands cmd-persistence install.sh:50
    Persistence mechanism (cron / launchd / scheduled task / autorun registry)
    (crontab -l 2>/dev/null; echo "7 3 * * * $UPDATE_CMD") | crontab -
Medium and low: 10
  • medium Exfiltration net-redirectable-api-key bot-server/ai_client.py:41
    Helper sends the API key to a host configured by an environment variable — the key can be redirected to another server
    API key + configurable base URL from environment
  • medium Dangerous commands cmd-pipe-to-shell-known-host README_EN.md:16
    Pipe-to-shell installer from a well-known host (still executes remote code)
    curl -sSL https://raw.githubusercontent.com/Liubuq-sys/wenqisheng-ear-care-skill/main/install.sh | bash
  • medium Dangerous commands cmd-pipe-to-shell-known-host README.md:18
    Pipe-to-shell installer from a well-known host (still executes remote code)
    curl -sSL https://raw.githubusercontent.com/Liubuq-sys/wenqisheng-ear-care-skill/main/install.sh | bash
  • low Exfiltration read-dotenv bot-server/main.py:8
    Reads a .env file (quoted — discussed, not commanded)
    cp .env.example .env  # 编辑填好 API Key
    quoted
  • low Exfiltration read-dotenv bot-server/README.md:14
    Reads a .env file
    cp .env.example .env
  • low Dangerous commands cmd-pipe-to-shell-known-host install.sh:6
    Pipe-to-shell installer from a well-known host (still executes remote code) (code comment)
    #   curl -sSL https://raw.githubusercontent.com/Liubuq-sys/wenqisheng-ear-care-skill/main/install.sh | bash
    comment
  • low Dangerous commands cmd-cron-mention install.sh:49
    Mentions editing / listing crontab
    if ! crontab -l 2>/dev/null | grep -q "auto_update.sh"; then
  • low Dangerous commands cmd-cron-mention install.sh:50
    Mentions editing / listing crontab
    (crontab -l 2>/dev/null; echo "7 3 * * * $UPDATE_CMD") | crontab -
  • low Dangerous commands cmd-pipe-to-shell-known-host README_EN.md:38
    Pipe-to-shell installer from a well-known host (still executes remote code) (quoted — discussed, not commanded)
    → If not: run 'bash -c "curl -sSL https://raw.githubusercontent.com/Liubuq-sys/wenqisheng-ear-care-skill/main/install.sh | bash"'
    quoted
  • low Dangerous commands cmd-pipe-to-shell-known-host README.md:40
    Pipe-to-shell installer from a well-known host (still executes remote code) (quoted — discussed, not commanded)
    → 如不存在，运行: bash -c 'curl -sSL https://raw.githubusercontent.com/Liubuq-sys/wenqisheng-ear-care-skill/main/install.sh | bash'
    quoted

Files scanned: 29. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • note frontmatter-key unknown frontmatter key "homepage"

Process rating: all ten parameters 53/100

  • 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
  • 100Tools and files. No external tools needed
  • 100Steps. 100 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1528 tokens
  • 100Running it twice. No mutating operations

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
  • +4No input/output examples
  • -215 emoji in the instructions: noise for the model
  • -36 of 6 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 169: enough signal without eating the budget
  • +4Structure: 20 headings
  • +3Step-by-step instructions: 100 items
  • +4Reference files are cited in the instructions (5 of 5)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 66.

External checks

ClawHub: suspicious
The skill has a real customer-service purpose, but it also installs self-updating code, changes agent behavior on broad keywords, and contains unrelated development-bot functionality that users should review before installing.
LLM: suspicious (high) · VirusTotal: · 29 May 2026