BB alibabacloud-error-troubleshoot
Alibaba Cloud OpenAPI troubleshooting skill. Use this skill when the user needs to diagnose API call failures using Request ID, error codes, or error messages — via Aliyun CLI `openapiexplorer` plugin commands. Triggers: "RequestId 排查", "Request ID 诊断", "错误码解决方案", "API 调用失败", "get-request-log", "get-own-request-log", "get-error-code-solutions", "OpenAPI 故障排查", "API troubleshoot", "diagnose OpenAPI", "diagnose OpenAPI error codes", "diagnose OpenAPI error messages", "Diagnose OpenAPI API call failures using Request ID".
Alibaba Cloud OpenAPI troubleshooting skill.
As a process B 70/100 · Nearly there — weak spots: result and completion
What is at stake
The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.
The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.
Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.
How to improve
- Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
- 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 · 1
-
high Dangerous commands
cmd-pipe-to-shellreferences/cli-installation-guide.md:16Downloads and executes remote code from an unrecognised host (pipe to shell)curl -fsSL https://aliyuncli.alicdn.com/setup.sh | bash
Files scanned: 6. 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 70/100
- 0Result and completion. Does not say what the result is
- 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
- 70When it triggers. States when to use, but not when not to
- 70Inputs and preconditions. Inputs and preconditions are listed
- 85Steps. 43 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 3643 tokens
- 100Running it twice. No mutating operations
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
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
- +1No license
- +2Single-language instructions
- +5Description quotes 13 example trigger phrases
- +3Description length 524: enough signal without eating the budget
- +4Structure: 17 headings
- +3Step-by-step instructions: 43 items
- +4Has examples (7 code blocks)
- +4Reference files are cited in the instructions (4 of 4)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 93.