SKILLEMALL.ai

AC green-vault

AI Agent 安全与绿色运维顾问。合并 EcoCompute(GPU 能耗优化)与 OpenClaw/Bagman(安全密钥管理), 提供 LLM 推理部署的能效分析、密钥安全管理、泄露防护和注入防御一体化方案。 Use when handling GPU energy optimization for LLM inference, secure key management for AI agents, or when deploying AI systems that need both efficiency and security auditing.

ClawHub Agent Skills author: hongping-zh v1.0.0 MIT-0 7 files body ≈ 2 453 tokens Open the sourceclawhub.ai analyzed 4 d ago

As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerAI and agentsInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
93/100
safety, quality, tests
Safety 60%
99
Quality 40%
85
Run on models
none yet
Process rating
C
51/100
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

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

    ✓ Guard found no suspicious behaviour. 1 matches are attack strings quoted in this security skill's own documentation.

    Files scanned: 7. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "homepage"

    Process rating: all ten parameters 51/100

    • 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. 5 mutating operations with no state check
    • 100Tools and files. No external tools needed
    • 100Steps. 71 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2453 tokens

    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
    • -228 emoji in the instructions: noise for the model
    • +1No license
    • +2Single-language instructions
    • +3Description length 284: enough signal without eating the budget
    • +4Structure: 39 headings
    • +3Step-by-step instructions: 71 items
    • +4Has examples (17 code blocks)
    • +4Reference files are cited in the instructions (5 of 5)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 85.

    External checks

    ClawHub: clean
    Green Vault is a disclosed operations guide for GPU efficiency and secret management, with sensitive examples that are expected for its purpose but should be run carefully.
    LLM: benign (high) · VirusTotal: suspicious · 28 May 2026