BC ops-dashboard-free
运维看板免费版是一款面向个人开发者和小团队的实时运维监控辅助Skill，让AI Agent能够查看会话状态、监控定时任务执行情况和检查系统健康度，实现轻量级的运维可视化。核心能力：会话列表查看、定时任务状态监控、网关健康检查、基础安全扫描、配置文件管理。Use
运维看板免费版是一款面向个人开发者和小团队的实时运维监控辅助Skill，让AI Agent能够查看会话状态、监控定时任务执行情况和检查系统健康度，实现轻量级的运维可视化。核心能力：会话列表查看、定时任务状态监控、网关健康检查、基础安全扫描、配置文件管理。Use
As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
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 instructions or scripts send data out: environment variables, keys, file contents, chat history. You may never notice, because the agent performs the upload as "part of the task".
If the upload is not needed for the task, remove it: catalogs flag such skills and delist them. If it is needed, name the destination explicitly, say what leaves the machine, and give the user a switch.
How to improve
- 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 Exfiltration
net-credential-useSKILL.md:161Credential used in a network call (verify the destination is the intended service)curl -H "Authorization: Bearer $OPS_DASHBOARD_AUTH_TOKEN" \
Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
frontmatter-yamlSKILL.md: the frontmatter is not valid YAML (YAML parse error: Map keys must be unique at line 22, column 1: suggested_price: "19.9 CNY/per_use" tools: ["read", "write", "exec"] ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value - note
frontmatter-keyunknown frontmatter key "slug" - note
frontmatter-keyunknown frontmatter key "displayName" - note
frontmatter-keyunknown frontmatter key "summary" - note
frontmatter-keyunknown frontmatter key "edition" - note
frontmatter-keyunknown frontmatter key "tools" - note
frontmatter-keyunknown frontmatter key "homepage" - note
frontmatter-keyunknown frontmatter key "pricing_tier" - note
frontmatter-keyunknown frontmatter key "pricing_model" - note
frontmatter-keyunknown frontmatter key "suggested_price"
Process rating: all ten parameters 53/100
- 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
- 20When it triggers. No condition that starts the skill
- 100Tools and files. Tools declared in frontmatter
- 100Steps. 29 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1516 tokens
- 100Running it twice. No mutating operations
- low 11 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
- -2localhost URLs: will not work for another user
- +2Single-language instructions
- +3Description length 130: enough signal without eating the budget
- +4Structure: 36 headings
- +3Step-by-step instructions: 29 items
- +4Has examples (9 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 70.