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BD wsl-service-deploy

WSL Ubuntu 服务一键部署。通过 wsl.exe + su -c root + aptitude，无需 SSH 即可在 Windows 宿主机上安全、快速地安装和管理后端服务。 覆盖 MySQL、Redis、Nginx、PostgreSQL、MongoDB 等任意 aptitude 可搜到的包。适用场景：WSL 运维、服务安装、环境搭建。

ClawHub Agent Skills author: microsnow v0.1.0 MIT-0 4 files body ≈ 750 tokens Open the sourceclawhub.ai↗ analyzed 19 h ago

WSL Ubuntu 服务一键部署。通过 wsl.exe + su -c root + aptitude，无需 SSH 即可在 Windows 宿主机上安全、快速地安装和管理后端服务。 覆盖 MySQL、Redis、Nginx、PostgreSQL、MongoDB 等任意 aptitude…

As a process D 45/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureMySQLPostgreSQLMongoDBInfrastructuretype 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
89/100
safety, quality, tests
Safety 60%
99
Quality 40%
75
Run on models
none yet
Process rating
D
45/100
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

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 · 1

✓ No critical or high findings

Medium and low: 1
  • low Dangerous commands cmd-background-process README.md:26
    Starts a background / autostarted process
    └─ systemctl enable  ← 配开机自启

Files scanned: 1. 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 "agent_created"

Process rating: all ten parameters 45/100

  • 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
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 1 mutating operations with no state check
  • 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
  • 100Steps. 38 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 750 tokens
  • 100Progress reporting. Reports progress
  • low The response is described with custom markup (7 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
  • +1No license
  • +2Single-language instructions
  • +3Description length 174: enough signal without eating the budget
  • +4Structure: 13 headings
  • +3Step-by-step instructions: 38 items
  • +4Has examples (3 code blocks)
  • +4Reference files are cited in the instructions (1 of 1)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.

External checks

ClawHub: suspicious
This skill is for WSL service deployment, but it teaches unsafe root access, weak default credentials, externally exposed services, and destructive cleanup commands.
LLM: suspicious (high) · 14 Jun 2026