AB huawei-cloud-cce-change-impact-analyzer
Huawei Cloud CCE change impact analysis skill that converts "what changed before the incident" into provable causal attribution. Use this skill when a CCE incident may be caused by recent changes, including workload releases, ConfigMap/Secret updates, Service/Ingress/Gateway route changes, NetworkPolicy/RBAC/security policy changes, node taints or infrastructure changes, and the user needs a complete Markdown report with timeline, evidence matrix, blast radius, risk score, and conclusion. Trigger: "change impact analysis", "变更影响分析", "change risk", "变更风险", "deployment impact", "发布影响", "config change", "配置变更", "network policy change", "网络策略变更", "node taint change", "节点污点变更", "blast radius", "爆炸半径", "recent changes", "近期变更", "audit log correlation", "审计日志关联"
Huawei Cloud CCE change impact analysis skill that converts "what changed before the incident" into provable causal attribution.
As a process B 68/100 · Nearly there — weak spots: 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 · 1
✓ No critical or high findings
Medium and low: 1
✓ Guard found no suspicious behaviour. 1 matches are attack strings quoted in this security skill's own documentation.
Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- note
frontmatter-keyunknown frontmatter key "id"
Process rating: all ten parameters 68/100
- 30Running it twice. 8 mutating operations with no state check
- 50When it triggers. No condition that starts the skill
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (bash, web, python, node) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 70Inputs and preconditions. Inputs and preconditions are listed
- 70Execution cost. Instruction body is 4272 tokens
- 100Steps. 56 steps
- 100Consistency. Name and required fields are in place
- 100Progress reporting. Reports progress
- 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)
- -31 of 2 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +5Description quotes 14 example trigger phrases
- +3Description length 765: enough signal without eating the budget
- +4Structure: 19 headings
- +3Step-by-step instructions: 56 items
- +3Output format is stated explicitly
- +4Has examples (1 code blocks)
- +4Reference files are cited in the instructions (4 of 4)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 92.