AC alibabacloud-oos-chatops-agent
Alibaba Cloud OOS ChatOps Agent for natural-language cloud resource management and O&M operations. Supports querying ECS/RDS/VPC/SLB resources, executing operations (start/stop/restart), viewing monitoring and billing data, and batch O&M via OOS. Use when users ask about Alibaba Cloud resources, instance management, cloud operations, or O&M automation. Triggers: "查看实例", "ECS", "RDS", "管理资源", "运维", "OOS", "ChatOps", "阿里云资源", "实例列表", "帮我操作", "重启", "停止实例", "resource management", "cloud operations", "list instances", "batch ops".
Alibaba Cloud OOS ChatOps Agent for natural-language cloud resource management and O&M operations.
As a process C 60/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, running it twice
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: 5. 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 60/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 1 mutating operations with no state check
- 60Tools and files. Uses tools (bash, web, python) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 85Steps. 25 steps, 1 vague phrases
- 100Failures and branches. 1 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1988 tokens
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 10 top-level sections: this looks like several domains in one skill
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)
- +1No license
- +2Single-language instructions
- +5Description quotes 5 example trigger phrases
- +3Description length 531: enough signal without eating the budget
- +4Structure: 11 headings
- +3Step-by-step instructions: 25 items
- +3Output format is stated explicitly
- +4Has examples (5 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 99.