model-based-testing · diff
git:20260915.d07a5f5 to git:20260915.f49090d
41 added, 17 removed. Audit A to A.
---
name: model-based-testing
description: Use this skill when you need to derive test-path candidates from sourced behavior, state, or process models; triggers include model-based test design.
---
# Model-Based Test Design
- derive test-path candidates from sourced behavior, state, or process models，输出 MBT-##。它只产生证据边界内的设计候选，不执行测试，不宣称覆盖或通过。
+ Derive test-path candidates from sourced behavior, state, or process models. Produce MBT-## design candidates within the evidence boundary; do not execute tests or claim coverage or pass results.
- ## 何时使用
+ ## When to Use
- - 需要分析 behavior models, states/nodes, events, path constraints, model version, and existing execution evidence。
- - 需要保留选择理由、证据缺口、优先级和验证动作。
- - 输入不完整但需要交付受限初版，并标记 unassessed 或 blocked。
+ - Analyze behavior models, states or nodes, events, path constraints, model versions, and existing execution evidence.
+ - Preserve selection rationale, evidence gaps, priority, and validation actions.
+ - Inputs are incomplete but a bounded first pass can mark items unassessed or blocked.
- ## 如何使用
+ ## Output Format Options
- 1. 阅读 prompts/model-based-testing.md，先列出 known、missing、conflicting、stale、out_of_scope、assumptions。
- 2. 按方法合同形成 MBT-##，保留来源、证据状态、影响、责任角色、关闭条件和验证方法。
- 3. 事实、推断、建议和 Human 决策必须分开。
- 4. 只提出后续验证意图，不写成已执行结果。
+ - Use Markdown by default; use tables, JSON, or CSV only when explicitly requested or required by the delivery format.
+ - Separate static analysis, unexecuted work, evidence states, and Human decisions; keep items unassessed, blocked, or NOT_RUN when runtime evidence is absent.
- ## 核心约束
+ ## How to Use
+ 1. Read `prompts/model-based-testing.md` and provide the objective, scope, material, environment, and evidence.
+ 2. Start with separate known, missing, conflicting, stale, out_of_scope, and assumptions entries.
+ 3. Produce MBT-## findings with source, evidence state, applicability, impact/priority, owner, close condition, and validation.
+ 4. Separate facts, evidence-backed inferences, recommendations, and Human decisions.
+ 5. Recommend follow-up validation without claiming execution.
+
+ ## Core Constraints
+
- Do not invent model nodes, paths, or versions, or treat model presence as runtime evidence.
- - 文件存在、名称、模板和 Eval 配置不等于真实执行证据。
- - 不修改需求、代码、测试资产或目标系统，不替 Human 接受风险。
+ - File presence, names, templates, and Eval configuration are not runtime evidence.
+ - Do not edit requirements, code, test assets, or target systems, or accept risk for a Human.
- ## 交付前自检
+ ## Pre-delivery Check
- - [ ] 六类输入审计完整。
- - [ ] 每条 MBT-## 有来源、证据、影响/优先级、责任角色、关闭条件和验证方法。
- - [ ] 已明确未执行、未验证、未评估和待决策项。
+ - [ ] The six-part input audit is complete.
+ - [ ] Every MBT-## has source, evidence state, applicability, concern, impact/priority, owner, close condition, and validation.
+ - [ ] Facts, inferences, recommendations, and Human decisions are separate.
+ - [ ] Unexecuted, unverified, unassessed, and pending-decision items are explicit.
+
+ ## Reference Files
+
+ - Read evals/eval.yaml and matching cases for regression; configuration does not prove project results.
+ - Use evals/trigger-prompts.csv and evals/local-rules.json for trigger checks; missing skill.selection evidence is BLOCKED.
+
+ ## Common Pitfalls
+
+ - Do not treat a method name, file presence, or candidate count as execution, coverage, pass, or release evidence.
+ - Do not fill missing model rules, paths, versions, or results with convention; preserve unassessed, blocked, and pending items.
+ - Do not expand this specialist design into a complete strategy, full test cases, runtime execution, or a release decision.
+
+ ## Best Practices
+
+ - Complete the six-part input audit before selecting the smallest traceable and verifiable finding scope.
+ - Keep the source, evidence state, impact/priority, owner role, close condition, validation method, and residual risk for every finding.
+ - Write validation suggestions as next actions; do not upgrade package structure, candidate counts, or local Eval configuration into real quality conclusions.