AC alibabacloud-lb-healthcheck
Read-only health-check diagnostics for Alibaba Cloud load balancers (CLB/ALB/NLB). Collects listener health-check configuration, forwarding rules, server groups and backend server probe status, and produces a structured diagnosis report; never changes any configuration. Use when health checks fail, backend servers are marked unhealthy, or the customer asks about load balancer health-check configuration. Triggers: "health check failed", "unhealthy backend server", "backend probe abnormal", "backend server unhealthy", "SLB health check diagnosis", "CLB health check diagnosis", "ALB health check diagnosis", "NLB health check diagnosis", "listener health check configuration query", "server group probe status".
Read-only health-check diagnostics for Alibaba Cloud load balancers (CLB/ALB/NLB).
As a process C 62/100 · Has gaps — weak spots: result and completion
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: 15. 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 62/100
- 0Result and completion. Does not say what the result is
- 50When it triggers. No condition that starts the skill
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (bash, web, python) that frontmatter does not declare
- 70Inputs and preconditions. Inputs and preconditions are listed
- 85Steps. 43 steps, 2 vague phrases
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3805 tokens
- 100Running it twice. Mutating operations check current state
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 13 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (4 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
- +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
- -31 of 4 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +5Description quotes 10 example trigger phrases
- +3Description length 715: enough signal without eating the budget
- +4Structure: 19 headings
- +3Step-by-step instructions: 43 items
- +4Has examples (2 code blocks)
- +4Reference files are cited in the instructions (8 of 8)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.