AD generate-model-ready-test-cases-cn
生成标准化、模型可直接消费的自动化测试用例 JSON 套件。用于 Codex 需要根据需求文档、原型图、页面说明、接口文档、用户故事、缺陷描述或自然语言需求，产出可直接交给其他模型或自动化代理执行的测试用例时；尤其适用于 Web UI、API、端到端流程、回归、冒烟和验收场景。
As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
IntegrationSoftware developmentInfrastructuretype and topics are labelled automatically from the skill text
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
For the model run — optional
- 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: 6. 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")
Process rating: all ten parameters 46/100
- 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
- 60Tools and files. Uses tools (web) that frontmatter does not declare
- 100Steps. 72 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 816 tokens
- 100Running it twice. No mutating operations
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
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +3Description length 139: enough signal without eating the budget
- +4Structure: 16 headings
- +3Step-by-step instructions: 72 items
- +4Reference files are cited in the instructions (2 of 2)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.
External checks
ClawHub: clean
This skill is a focused Chinese test-case generator with a local JSON validator and no evidence of hidden access, persistence, or unsafe behavior.
LLM: benign (high) · VirusTotal: · 29 May 2026