SKILLEMALL.ai

AB universal-shell-deployer

Install, configure, start, stop, and verify local or remote development infrastructure across Windows, Linux, and macOS by executing commands through a unified workflow. Use when the user asks to set up databases, MinIO, ZLMediaKit, Docker, Redis, PostgreSQL, MySQL, Nginx, Node.js, Java, or other developer environments on local machines or remote hosts.

ClawHub Agent Skills author: hgvgfgvh v1.0.0 MIT-0 3 files body ≈ 1 311 tokens Open the sourceclawhub.ai analyzed 2 d ago

As a process B 79/100 · Nearly there — no weak spots found

AnalyzerDockerPostgreSQLMySQLInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
98
Quality 40%
87
Run on models
none yet
Process rating
B
79/100
Nearly there
Tools and files w 18
60
Result and completion w 14
60
Inputs and preconditions w 11
70
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 · 2

    ✓ No critical or high findings

    Medium and low: 2
    • low Risky intent intent-offensive-security skill-card.md:21
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      Mitigation: Review the proposed command plan before execution, run changes in small verified steps, and approve privilege escalation explicitly. <br>
    • low Risky intent intent-offensive-security SKILL.md:162
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      - Surface privilege escalation clearly before executing privileged commands.

    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 79/100

    • 60Tools and files. Uses tools (bash, node) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 70Failures and branches. 4 branches
    • 85Steps. 95 steps, 1 vague phrases
    • 100When it triggers. States when to use and when not to
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1311 tokens
    • 100Running it twice. Mutating operations check current state
    • 100Progress reporting. Reports progress
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • low 10 top-level sections: this looks like several domains in one skill
    • low The response is described with custom markup (8 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)
    • +1No license
    • +2Single-language instructions
    • +3Description length 355: enough signal without eating the budget
    • +4Structure: 21 headings
    • +3Step-by-step instructions: 95 items
    • +3Output format is stated explicitly
    • +4Has examples (0 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.

    External checks

    ClawHub: suspicious
    This skill is transparent about running deployment commands, but it needs review because it can change local or remote systems and includes unsafe default administrative credentials.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026