qa-archive
Skill0 starsChanged 3 months agoMITView on GitHub
在一次变更 / 测试周期结束时使用,把全部产物(需求、用例、执行结果、报告、缺陷) 打包成一个带时间戳与清单 manifest 的归档,使整个测试生命周期可追溯、可复盘、 可还原交付审计。触发词:"归档"、"一键归档"、"测试归档"、"关闭变更",或在 qa-release-check 通过之后使用。 英文触发词(English triggers):test archive, change closure, test artifacts.
In this repository39 other files it gives its agents.
- qa-a11ySkill
- qa-agent-evalSkill
- qa-agent-securitySkill
- qa-api-contractSkill
- qa-api-docSkill
- qa-api-runnerSkill
- qa-bug-reportSkill
- qa-bug-verifySkill
- qa-chaosSkill
- qa-ciSkill
- qa-code-reviewSkill
- qa-compat-matrixSkill
- qa-env-configSkill
- qa-executionSkill
- qa-exploratorySkill
- qa-flaky-detectSkill
- qa-mobile-autotestSkill
- qa-mutationSkill
- qa-orchestratorSkill
- qa-perf-analysisSkill
- qa-perf-designSkill
- qa-perf-jmeterSkill
- qa-perf-locustSkill
- qa-release-checkSkill
- qa-reportSkill
- qa-req-specSkill
- qa-risk-basedSkill
- qa-security-reportSkill
- qa-security-scanSkill
- qa-synthetic-monitoringSkill
- qa-test-analysisSkill
- qa-test-case-genSkill
- qa-test-dataSkill
- qa-test-strategySkill
- qa-ui-automationSkill
- qa-ui-kbSkill
- qa-ui-testidSkill
- qa-unit-tddSkill
- qa-visual-regressionSkill
The file
Files
qa-archive — 一键归档
一个变更走完「需求→设计→测试→缺陷→上线」后,把整套产物打包成一个带清单的归档, 保证全流程可追溯、可复盘、可交付审计。
测试的价值一半在结论,一半在可追溯。归档让每次发布都有完整证据链。
何时使用
- 变更关闭 / 上线完成 / 版本发布。
- 用户说「归档」「一键归档」「测试归档」「关闭变更」。
操作流程
步骤 1 — 指定变更目录
变更目录由 qa-orchestrator 的 init_change.py 创建,含 01-requirement … 08-archive。
步骤 2 — 归档
python scripts/archive_change.py --change changes/登录模块v2 --out ./archives产出 ./archives/登录模块v2_20260805_215200.zip(含全部产物,排除缓存)+
登录模块v2_..._manifest.md(目录树 + 文件数 + 大小 + 关键结论摘要占位)。
步骤 3 — 交付 / 审计
归档文件可作版本发布附件、等保/审计证据、团队知识库沉淀。
与上下游衔接
- 输入:
qa-orchestrator变更目录(上游所有产物)。 - 上游触发:
qa-release-check通过后归档。 - 事后:
qa-report结论已落进归档,便于回溯质量趋势。
参考资料
- 检查项、阈值、CLI 用法与常见坑:见
references/guide.md。
阶段产物契约(stages.json artifacts)
本阶段主技能须产出的文件名(与 qa-orchestrator/stages.json 契约一致):
- archive.zip
- ci.yaml
- test-strategy.md
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

