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AC hid-dock

Connect to and control the Acasis Flow HID dock hardware (VID=0x35e6 PID=0xa4ac, 64-byte reports). Use when: the user asks to connect, check, switch view/page, read from, or send to the HID dock / 扩展坞 / Flow View device. Switches the dock screen between 数据同步(dataSync) and 快捷操作(shortcuts), inspects connection, reads reports, and sends raw payloads. Windows only. NOT for: generic mouse/keyboard automation or other vendors' HID devices.

ClawHub Agent Skills author: facaiHero v1.1.0 MIT-0 3 files body ≈ 812 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

Connect to and control the Acasis Flow HID dock hardware (VID=0x35e6 PID=0xa4ac, 64-byte reports).

As a process C 62/100 · Has gaps — weak spots: result and completion, inputs and preconditions

IntegrationData and analyticstype 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
A
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
88
Run on models
none yet
Process rating
C
62/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
When it triggers w 12
50
the three weakest of ten parameters · all ten

How to improve

    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: 3. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 62/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 50When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 100Steps. 13 steps
    • 100Failures and branches. 2 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 812 tokens
    • 100Running it twice. Mutating operations check current state
    • 100Progress reporting. Reports progress

    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
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 437: enough signal without eating the budget
    • +4Structure: 11 headings
    • +3Step-by-step instructions: 13 items
    • +4Has examples (6 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.

    External checks

    ClawHub: suspicious
    This skill is purpose-aligned for controlling a specific HID dock, but it tells the agent to download and run an unverified Windows executable from GitHub on first use.
    LLM: suspicious (medium) · VirusTotal: · 9 Jul 2026