BF self-hosted-ai
自托管 AI 工具部署与运维助手。用于：(1) 在服务器上部署 Ollama（本地大模型）、N8N（自动化工作流）、Open WebUI 等 AI 工具，(2) 配置 Docker / Docker Compose 环境，(3) 管理模型下载和更新，(4) 排查服务故障，(5) 配置反向代理（nginx）和 HTTPS。当用户说"部署 Ollama"、"装 N8N"、"自己跑 AI"、"搭建本地大模型"、"自托管 AI 工具"时触发此技能。
自托管 AI 工具部署与运维助手。用于：(1) 在服务器上部署 Ollama（本地大模型）、N8N（自动化工作流）、Open WebUI 等 AI 工具，(2) 配置 Docker / Docker Compose 环境，(3) 管理模型下载和更新，(4) 排查服务故障，(5) 配置反向代理（nginx）和…
As a process F 34/100 · Will not run — weak spots: steps, result and completion, when it triggers
What is at stake
Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
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.
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
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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
-
medium Dangerous commands
cmd-pipe-to-shellSKILL.md:22Downloads and executes remote code from an unrecognised host (pipe to shell) (the skill's own vendor host)curl -fsSL https://ollama.com/install.sh | sh
vendor-host
Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 34/100
- 0Steps. Prose only: no discrete steps
- 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 (self-hosted-ai) differs from the folder (self-hosted-ai-2)
- 100Tools and files. No external tools needed
- 100Execution cost. Instruction body is 497 tokens
- 100Running it twice. No mutating operations
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
- +4Description does not say when NOT to use the skill (false activations)
- +3No numbered steps or checklist
- +3Output format is not stated: the model decides each time
- -2localhost URLs: will not work for another user
- +1No license
- +2Single-language instructions
- +5Description quotes 4 example trigger phrases
- +3Description length 222: enough signal without eating the budget
- +4Structure: 7 headings
- +4Has examples (4 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.