AD it-ops-toolkit
IT运维工具箱技能。覆盖网络诊断、系统监控、服务检查、监控问题排查、实用工具等核心运维场景。 适合运维工程师、开发人员日常使用。在 WorkBuddy 中通过自然语言触发，由 AI 选择合适的脚本执行并解读结果。 触发场景（包括但不限于）： - 网络/连通性：ping检测、DNS解析、**域名查IP**、HTTP检测、SSL证书检查、端口扫描、IP归属地查询 - 系统监控：CPU使用率、内存使用、磁盘空间、进程列表、系统负载、网卡信息、**远程服务器监控（SSH）** - 服务状态：Systemd服务、Windows服务、Docker容器状态、数据库连通性测试、Web健康检查 - 问题排查：日志扫描、OOM内存不足、进程崩溃、网络连接异常、性能瓶颈、**视频监控播放问题排查**、**视频取流测试**、**RTSP快捷取流**、根因分析 - 实用工具：密码生成、UUID生成、Token生成、Cron表达式解析、JSON格式化、Base64/JWT解码、时间戳转换、文件MD5/SHA256、正则测试
IT运维工具箱技能。覆盖网络诊断、系统监控、服务检查、监控问题排查、实用工具等核心运维场景。 适合运维工程师、开发人员日常使用。在 WorkBuddy 中通过自然语言触发，由 AI 选择合适的脚本执行并解读结果。 触发场景（包括但不限于）： -…
As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
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 · 0
✓ No critical or high findings
Files scanned: 8. 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") - note
frontmatter-keyunknown frontmatter key "slug"
Process rating: all ten parameters 46/100
- 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
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 100Steps. 22 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 684 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
- +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
- -4Absolute local paths (C:\Users, /home/…): not portable
- +2Single-language instructions
- +3Description length 454: enough signal without eating the budget
- +4Structure: 14 headings
- +3Step-by-step instructions: 22 items
- +4Has examples (3 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
- +3All 4 scripts are documented
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.