SKILLEMALL.ai

BD minimal-agent

极简 AI 操作系统控制代理。通过执行协议驱动 system-controller 完成窗口管理、进程控制、硬件操作、GUI自动化、串口通信和IoT设备交互。 当用户需要操控 Windows 系统(打开/关闭应用、调整音量亮度、 截图OCR、管理进程、串口通信等)时使用此 Skill。 触发词:打开应用、关闭窗口、调音量、调亮度、锁屏、关机、 列出进程、发串口命令、控灯、连Arduino、开WiFi、USB设备、 截屏、OCR、找图点击、输入文字、鼠标操作等。

ClawHub Agent Skills author: 波动几何 v1.0.0 MIT-0 4 files body ≈ 1 962 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process D 43/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureAI and agentsInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
88/100
safety, quality, tests
Safety 60%
100
Quality 40%
71
Run on models
none yet
Process rating
D
43/100
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 · 0

✓ No critical or high findings

Files scanned: 4. 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")

Process rating: all ten parameters 43/100

  • 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. 2 mutating operations with no state check
  • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
  • 100Steps. 62 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1962 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

  • +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
  • -4Absolute local paths (C:\Users, /home/…): not portable
  • +1No license
  • +2Single-language instructions
  • +3Description length 233: enough signal without eating the budget
  • +4Structure: 27 headings
  • +3Step-by-step instructions: 62 items
  • +4Has examples (8 code blocks)
  • +3All 1 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.

External checks

ClawHub: suspicious
This skill is a powerful system-control agent that openly supports arbitrary command execution and automatic fallback into that mode, so users should review it carefully before installing.
LLM: suspicious (high) · VirusTotal: · 29 May 2026