SKILLEMALL.ai
GitHub ↗ RU Sign in

AD caprover

Manage CapRover PaaS instances via API: create/update apps, deploy from Docker image or custom Dockerfile (tar file), configure ports, volumes, env vars, and serviceUpdateOverride for Docker Swarm settings. Use when the user wants to deploy, configure, or diagnose an app on a CapRover server — including setting up TCP ports for non-HTTP servers (game servers, databases), mounting persistent volumes, building custom Docker images on the host, or reading build/runtime logs.

ClawHub Agent Skills author: Thiago Guimarães v1.0.0 4 files body ≈ 1 396 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process D 48/100 · Unfinished process — weak spots: result and completion, inputs and preconditions, failures and branches

IntegrationDockerInfrastructuretype 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
96/100
safety, quality, tests
Safety 60%
99
Quality 40%
91
Run on models
none yet
Process rating
D
48/100
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 · 1

    ✓ No critical or high findings

    Medium and low: 1
    • low Secrets in code secret-high-entropy-token scripts/caprover.py:144
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      boundary = "----…4YW"
      quoted

    Files scanned: 4. 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 48/100

    • 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
    • 30Running it twice. 4 mutating operations with no state check
    • 40Consistency. Frontmatter name (caprover) differs from the folder (caprover-management)
    • 60Tools and files. Uses tools (python, node) that frontmatter does not declare
    • 100Steps. 6 steps
    • 100When it triggers. States when to use and when not to
    • 100Execution cost. Instruction body is 1396 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
    • +1No license
    • +2Single-language instructions
    • +3Description length 476: enough signal without eating the budget
    • +4Structure: 13 headings
    • +3Step-by-step instructions: 6 items
    • +4Has examples (8 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 91.

    External checks

    ClawHub: suspicious
    This is a coherent CapRover admin skill, but it tells agents to weaken HTTPS protection while handling powerful server credentials.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026