AC aliyun-oidc-cert-renew
用 GitHub Actions + 阿里云 RAM OIDC 自动续期 Let's Encrypt 通配证书并分发到 OSS/FC/CDN，仓库零长期 AK。覆盖 OIDC 提供商/角色/权限策略搭建、workflow 手动兑换临时 STS、ACME DNS-01 签发、CAS 上传复用、新子域 DNS 自动发现绑定、60 天 keepalive、状态持久化，以及 IMS/RAM/CAS/oss2 SDK 的全部命名坑。当用户说「自动续期证书」「不想存 AK」「GitHub Actions 操作阿里云」「SSL 证书过期」「新增子域自动上 HTTPS」「免密钥访问阿里云」时使用。
用 GitHub Actions + 阿里云 RAM OIDC 自动续期 Let's Encrypt 通配证书并分发到 OSS/FC/CDN，仓库零长期 AK。覆盖 OIDC 提供商/角色/权限策略搭建、workflow 手动兑换临时 STS、ACME DNS-01 签发、CAS 上传复用、新子域 DNS…
As a process C 51/100 · 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.
- 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: 7. 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 "agent_created"
Process rating: all ten parameters 51/100
- 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
- 30Running it twice. 12 mutating operations with no state check
- 100Tools and files. No external tools needed
- 100Steps. 27 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2446 tokens
- low 11 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (9 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)
- +3Output format is not stated: the model decides each time
- +2Single-language instructions
- +3Description length 294: enough signal without eating the budget
- +4Structure: 15 headings
- +3Step-by-step instructions: 27 items
- +4Has examples (10 code blocks)
- +3All 2 scripts are documented
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.