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BC headscale-deploy

Deploy, configure, and maintain a self-hosted Headscale control server on Linux or Docker. Use when setting up a new Headscale instance, troubleshooting deployment issues, or configuring server settings.

magnus919/agent-skills Agent Skills author: magnus919 MIT 6 files · 3 scripts body ≈ 1 155 tokens Open the sourcegithub.com↗ analyzed 27 h ago

Deploy, configure, and maintain a self-hosted Headscale control server on Linux or Docker.

As a process C 62/100 · Has gaps — weak spots: result and completion, failures and branches, running it twice

IntegrationDockerPostgreSQLInfrastructuretype and topics are labelled automatically from the skill text
Runs in: 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) OpenClaw Goose OpenCode
JSON
Technical rating
B
92/100
safety, quality, tests
Safety 60%
99
Quality 40%
82
Run on models
none yet
Process rating
C
62/100
Has gaps
Result and completion w 14
0
Failures and branches w 10
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • 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 scripts/install-headscale.sh:257
      Starts a background / autostarted process
      systemctl enable headscale.service

    Files scanned: 5. 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
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 12 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Tools and files. No external tools needed
    • 100Steps. 27 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1155 tokens
    • medium 6 test cases, all positive: not one "should refuse" or "should ask first"
    • low No test case covers injection arriving through data

    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
    • -31 of 3 scripts are never mentioned in SKILL.md
    • +2Single-language instructions
    • +3Description length 203: enough signal without eating the budget
    • +4Structure: 11 headings
    • +3Step-by-step instructions: 27 items
    • +4Has examples (2 code blocks)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.