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BC ansible

Infrastructure automation with Ansible. Use for server provisioning, configuration management, application deployment, and multi-host orchestration. Includes playbooks for OpenClaw VPS setup, security hardening, and common server configurations.

Not recommendedcritical or high security findings
modbender/skill-library-mcp Agent Skills author: modbender MIT 20 files body ≈ 2 695 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Infrastructure automation with Ansible.

As a process C 54/100 · Has gaps — weak spots: result and completion, when it triggers, consistency

ProcedureInfrastructuretype 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
B
80/100
safety, quality, tests
Safety 60%
74
Quality 40%
88
Run on models
none yet
Process rating
C
54/100
Has gaps
Result and completion w 14
0
Progress reporting w 2
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

What is at stake

The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.

Secrets in code
If you install

The files contain someone else's key or token. If it is live, your agent will call third-party services under a stranger's identity; if it was revoked, the skill's scripts simply fail. Such a key often arrives with the author's whole workspace, personal data included.

For the author

The key is visible to everyone who downloaded the skill and has likely been copied by catalog-scanning bots already. Revoke it now, check bills and access logs, then reissue.

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

  1. Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
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 · 5

  • high Secrets in code secret-private-key SKILL.md:267
    Private key material (key header without key body)
    -----BEGIN PRIVATE KEY----- …
    header only
Medium and low: 4
  • medium Dangerous commands cmd-persistence references/modules-cheatsheet.md:127
    Persistence mechanism (cron / launchd / scheduled task / autorun registry) (documentation of a security skill)
    path: /etc/crontab
    security skill
  • low Dangerous commands cmd-background-process playbooks/openclaw-vps.yml:290
    Starts a background / autostarted process
    sudo systemctl enable --now openclaw
  • low Dangerous commands cmd-background-process playbooks/openclaw-vps.yml:338
    Starts a background / autostarted process
    4. sudo systemctl enable --now openclaw
  • low Dangerous commands cmd-background-process roles/openclaw/tasks/main.yml:88
    Starts a background / autostarted process
    ║  4. Enable service: sudo systemctl enable --now openclaw         ║

Files scanned: 20. 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 54/100

  • 0Result and completion. Does not say what the result is
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 40Consistency. Frontmatter name (ansible) differs from the folder (ansible-skill)
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (bash, node) that frontmatter does not declare
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Steps. 29 steps
  • 100Execution cost. Instruction body is 2695 tokens
  • 100Running it twice. No mutating operations
  • low 12 top-level sections: this looks like several domains in one skill

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 245: enough signal without eating the budget
  • +4Structure: 39 headings
  • +3Step-by-step instructions: 29 items
  • +4Has examples (23 code blocks)
  • +4Reference files are cited in the instructions (3 of 3)

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