BC k8s-fta-skill
基于FTA故障树分析法的Kubernetes问题定位和修复工具。当用户遇到k8s集群问题、Pod运行异常、服务访问失败、RBAC权限问题、DNS解析失败、OOMKilled、健康检查失败、网络策略限制、存储挂载问题、HPA扩展问题、API Server连接问题等情况时，使用此技能自动执行kubectl命令进行故障排查和修复。同时支持k3s轻量级Kubernetes发行版的故障排查。Supports both Chinese and English troubleshooting and automated fixing for Kubernetes cluster issues including Pod failures, service access problems, RBAC issues, DNS resolution failures, OOMKilled, health check failures, network policy restrictions, storage mount issues, HPA scaling problems, and API Server connectivity issues. Also supports k3s lightweight Kubernetes distribution.
As a process C 53/100 · Has gaps — 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.
- 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: 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 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. No external tools needed
- 100Steps. 239 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3185 tokens
- 100Running it twice. No mutating operations
- low The response is described with custom markup (12 tags): a typed call is more reliable
- medium 20 test cases, all positive: not one "should refuse" or "should ask first"
- low No test case covers injection arriving through data
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 577: enough signal without eating the budget
- +4Structure: 43 headings
- +3Step-by-step instructions: 239 items
- +4Has examples (30 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.