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AC devops-deploy

Deploy applications and set up infrastructure. Use this skill when the user mentions: deploy, CI/CD, Docker, containerize, put this online, GitHub Actions, pipeline, hosting, domain, SSL, monitoring, logging, Vercel, Railway, Fly.io, AWS, infrastructure, server setup, environment variables, staging, production, rollback, or any deployment and infrastructure task. Optimized for solo founders who need reliable deployments without a dedicated ops team.

ClawHub Agent Skills author: Emerson Braun v1.0.0 MIT-0 3 files body ≈ 1 165 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 60/100 · Has gaps — weak spots: result and completion, inputs and preconditions, consistency

ProcedureDockerGitHubAWSInfrastructuretype 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
92/100
safety, quality, tests
Safety 60%
94
Quality 40%
88
Run on models
none yet
Process rating
C
60/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Dangerous commands medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.

For the author

Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.

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
    • medium Dangerous commands cmd-pipe-to-shell-known-host references/deployment-guides.md:59
      Pipe-to-shell installer from a well-known host (still executes remote code)
      curl -L https://fly.io/install.sh | sh
    • low Exfiltration read-dotenv SKILL.md:117
      Reads a .env file
      # Copy .env.example and fill in real values

    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 60/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 12 mutating operations with no state check
    • 40Consistency. Frontmatter name (devops-deploy) differs from the folder (eb-devops-deploy)
    • 70When it triggers. States when to use, but not when not to
    • 85Steps. 20 steps, 1 vague phrases
    • 100Tools and files. No external tools needed
    • 100Failures and branches. 2 branches, has a failure section
    • 100Execution cost. Instruction body is 1165 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 453: enough signal without eating the budget
    • +4Structure: 11 headings
    • +3Step-by-step instructions: 20 items
    • +4Has examples (4 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)

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

    External checks

    ClawHub: clean
    This is a straightforward DevOps deployment guide; its high-impact examples are visible and aligned with deployment work.
    LLM: benign (high) · VirusTotal: · 29 May 2026