BF alibabacloud-ecs-disaster-recovery-image
阿里云 ECS 跨可用区灾备恢复技能。从现有 ECS 实例创建系统镜像，并在不同可用区部署新实例。 当用户提到以下场景时使用：可用区故障恢复、跨可用区备份、跨可用区实例克隆、ECS 灾备、 用镜像在其他可用区创建实例、"帮我做个镜像然后换个可用区创建实例"等。 也适用于：灾备实例、镜像备份、换个可用区创建实例、可用区容灾、 制作镜像、跨可用区创建、从镜像创建实例。 注意：本技能是"备份"而非"迁移"，不会释放或影响原始实例的资源。
阿里云 ECS 跨可用区灾备恢复技能。从现有 ECS 实例创建系统镜像，并在不同可用区部署新实例。 当用户提到以下场景时使用：可用区故障恢复、跨可用区备份、跨可用区实例克隆、ECS 灾备、 用镜像在其他可用区创建实例、"帮我做个镜像然后换个可用区创建实例"等。…
As a process F 49/100 · Will not run — References files that are not bundled: references/ram-policies.md, references/verification-method.md, references/acceptance-criteria.md
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.
- The text references files that are not there: add them or drop the references.
- 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: 0. 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 ≈ 5319 tokens (recommended < 5000); move details to references/ - warning
missing-refreference to a missing file: references/ram-policies.md - warning
missing-refreference to a missing file: references/verification-method.md - warning
missing-refreference to a missing file: references/acceptance-criteria.md
Process rating: all ten parameters 49/100
- 0Tools and files. 3 referenced file(s) missing: references/ram-policies.md, references/verification-method.md, references/acceptance-criteria.md
- 0Inputs and preconditions. Does not say what the process needs to start
- 40Result and completion. Does not say what the result is
- 50When it triggers. No condition that starts the skill
- 60Steps. 17 steps, 4 vague phrases
- 70Execution cost. Instruction body is 5319 tokens
- 100Failures and branches. 1 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 (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
- +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 217: enough signal without eating the budget
- +4Structure: 25 headings
- +3Step-by-step instructions: 17 items
- +4Has examples (14 code blocks)
- +4Reference files are cited in the instructions (2 of 2)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 54.