CB alibabacloud-nginx-ingress-to-alb-ingress
Alibaba Cloud ALB Ingress Migration Skill. Migrate Kubernetes nginx Ingress resources to Alibaba Cloud Application Load Balancer (ALB Ingress, requires AlbConfig + IngressClass + Ingress). Users provide Ingress YAML (paste, file, or directory) — no cluster access required. Covers annotation compatibility classification, ALB-native annotation mapping, instance/listener-side configuration, path and order semantics, AlbConfig + IngressClass + Ingress generation, and a migration report with DNS weighted cutover. Triggers: "nginx ingress migration", "ALB compatibility", "ALB support check", "ingress-nginx to ALB", "switch to Application Load Balancer", "AlbConfig generation", "nginx迁移ALB", "nginx 迁移 ALB", "ALB Ingress迁移", "ALB Ingress 迁移", "切换到 ALB", "替换为 ALB", "AlbConfig生成", "AlbConfig 生成", "ALB 配置清单", "Ingress兼容性分析", "Ingress 兼容性分析", "入口规则适配", "注解适配审查", "annotation兼容性", "annotation 兼容性", "迁移评估", "切换可行性", "Nginx Ingress 迁移", "迁移到 alb ingress", "转成 alb ingress", "转成 ALB Ingress", "迁移到 ALB", "ingress 迁移".
Alibaba Cloud ALB Ingress Migration Skill.
As a process B 71/100 · Nearly there — weak spots: result and completion, when it triggers, execution cost
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- 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: 11. 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") - warning
body-longSKILL.md body ≈ 15963 tokens (recommended < 5000); move details to references/ - note
edit-residuethe text marks something as outdated (lines 116, 246): check that old rules are not kept next to new ones — the full check reads the text for contradictions
Process rating: all ten parameters 71/100
- 20When it triggers. No condition that starts the skill
- 40Result and completion. Does not say what the result is
- 40Execution cost. Instruction body is 15963 tokens: crowds the task out of the window
- 60Tools and files. Uses tools (bash, web, python) that frontmatter does not declare
- 100Steps. 35 steps
- 100Inputs and preconditions. Inputs and preconditions are listed
- 100Failures and branches. 5 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 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 12 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (34 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)
- +3Description length 1014: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- -2105 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +5Description quotes 27 example trigger phrases
- +4Structure: 19 headings
- +3Step-by-step instructions: 35 items
- +4Has examples (5 code blocks)
- +4Reference files are cited in the instructions (7 of 7)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 69.