SKILLEMALL.ai
GitHub ↗ RU Sign in

AD jumpserver-skills

JumpServer V4.10 查询与分析 skill。Use when users ask to query assets/accounts/users/organizations/permissions, inspect access or governance, audit logins/sessions/commands/file transfers, diagnose config or organization issues, or analyze JumpServer usage data for a specific day or time range such as 使用报告、日报、某天使用情况、某天登录/会话/命令/传输情况、usage report, daily usage report, usage analysis, or JumpServer usage overview.

ClawHub Agent Skills author: 老广 v1.1.0 MIT-0 33 files body ≈ 1 150 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

As a process D 41/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerData and analyticsInfrastructureSecuritytype 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%
98
Quality 40%
88
Run on models
none yet
Process rating
D
41/100
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

    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 Exfiltration read-dotenv README.en.md:35
      Reads a .env file (documentation of a security skill)
      cp .env.example .env
      security skill
    • low Exfiltration read-dotenv README.md:35
      Reads a .env file (documentation of a security skill)
      cp .env.example .env
      security skill

    Files scanned: 33. 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 41/100

    • 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
    • 40Consistency. Frontmatter name (jumpserver-skills) differs from the folder (jumpserver)
    • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
    • 100Steps. 60 steps
    • 100Execution cost. Instruction body is 1150 tokens
    • 100Running it twice. No mutating operations
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

    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
    • +1No license
    • +2Single-language instructions
    • +3Description length 407: enough signal without eating the budget
    • +4Structure: 8 headings
    • +3Step-by-step instructions: 60 items
    • +4Has examples (1 code blocks)
    • +4Reference files are cited in the instructions (5 of 12)

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

    External checks

    ClawHub: suspicious
    This appears to be a real JumpServer reporting skill, but it needs review because it handles credentials and sensitive audit/admin data while auto-installing packages and disabling TLS verification by default.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026