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AB gpu-keepalive-with-keepgpu

Install and operate KeepGPU for GPU keep-alive with both blocking CLI and non-blocking service workflows. Use when users ask for keep-gpu command construction, start/status/stop session control, dashboard usage, tuning (--vram, --interval, --busy-threshold), installation from this repository, or troubleshooting keep sessions; do not use for repository development, code refactoring, or unrelated Python tooling.

ClawHub Agent Skills author: Wangmerlyn v1.0.0 3 files body ≈ 1 331 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process B 68/100 · Nearly there — weak spots: result and completion, progress reporting

IntegrationSoftware developmenttype 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
94/100
safety, quality, tests
Safety 60%
99
Quality 40%
86
Run on models
none yet
Process rating
B
68/100
Nearly there
Result and completion w 14
0
Progress reporting w 2
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 · 1

    ✓ No critical or high findings

    Medium and low: 1
    • low Dangerous commands cmd-background-process SKILL.md:170
      Starts a background / autostarted process
      nohup keep-gpu --gpu-ids 0 --vram 1GiB --interval 300 > keepgpu.log 2>&1 &

    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 68/100

    • 0Result and completion. Does not say what the result is
    • 0Progress reporting. Says nothing while it works
    • 50When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (bash, python, node) that frontmatter does not declare
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 26 steps
    • 100Failures and branches. 3 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1331 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
    • +3Output format is not stated: the model decides each time
    • -2localhost URLs: will not work for another user
    • +1No license
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 413: enough signal without eating the budget
    • +4Structure: 14 headings
    • +3Step-by-step instructions: 26 items
    • +4Has examples (17 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 86.

    External checks

    ClawHub: clean
    This is a coherent KeepGPU helper skill that gives disclosed install and run commands, with expected cautions around external packages and GPU resource use.
    LLM: benign (high) · VirusTotal: · 29 May 2026