AD hello-env
Zero-dependency Bash environment health check for Linux, macOS, containers, and K8s pods. Reports OS, current user, Node.js, Python3, basic tools (git/curl/jq/make/docker) with paths and versions, network (hostname, IP, inferred subnet), container/K8s detection with a configurable env-var probe, workdir and git status, optional config-file check, and PVC remount detection (device-number plus watch-dir count snapshot diff to catch silent K8s PersistentVolume reattach to a fresh disk). Three-layer config — CLI flags override env vars override defaults. Trigger when user wants to check the environment, verify a dev box is healthy, detect container or K8s context, look up local IP or subnet, see Node and Python versions, list installed basic tools, or watch for silent PVC rotation in K8s pods. Also triggers on 检查我的环境, 环境自检, hello-env, 查看系统信息, 环境有没有问题, IP 是多少, 在什么环境, PVC 换卷了吗, 基础工具检查, node 版本, 当前用户是谁.
Zero-dependency Bash environment health check for Linux, macOS, containers, and K8s pods.
As a process D 49/100 · Unfinished process — weak spots: result and completion, inputs and preconditions, failures and branches
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 · 0
✓ No critical or high findings
Files scanned: 4. 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 49/100
- 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
- 30Running it twice. 2 mutating operations with no state check
- 60Tools and files. Uses tools (bash, web, python, node) that frontmatter does not declare
- 70When it triggers. States when to use, but not when not to
- 100Steps. 10 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1310 tokens
- low The response is described with custom markup (6 tags): a typed call is more reliable
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)
- +3Description length 909: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- -217 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +4Structure: 12 headings
- +3Step-by-step instructions: 10 items
- +4Has examples (4 code blocks)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.