My testing agent remembers what it learned. Mostly.

Описание и применение

Автоматизированный агент, читающий тикеты Jira, генерирует шаги тестирования, выполняет их в реальном браузере, сравнивает скриншоты и обновляет статус тикета. Новая версия хранит рабочие скрипты и переиспользует их, удаляя неработающие, что ускоряет и экономит токены.

Задача

Automated testing of Jira tickets in a real browser was slow and costly because each step was regenerated from scratch, even for repeated actions.

Результат

The agent now reuses working automation code, discarding broken code, which reduces token usage and speeds up test execution while maintaining accuracy.

Рабочий процесс

• 1. Orchestrator receives Jira ticket ID, URL, and user email. 2. Orchestrator starts a browser session via BaaS and logs in. 3. Orchestrator fetches the Jira issue and comments. 4. LLM generates an ordered list of test steps in strict JSON. 5. For each step, orchestrator calls sub‑agent step_execution. 6. Sub‑agent takes a screenshot and HTML snapshot, identifies the page. 7. Sub‑agent checks memory for a matching step. 8. If found, reuse stored program; otherwise generate new program. 9. Sub‑agent runs the program in the browser, takes a post‑action screenshot. 10. LLM compares screenshots to expected result and returns verdict. 11. Sub‑agent updates memory: stores successful programs, deletes broken ones. 12. Orchestrator aggregates results, posts a comment to Jira, and if all passed, moves ticket to Done. 13. Browser session is terminated.

Доказательства

An open-source agent that reads a Jira ticket, writes test steps, runs them in a real Chrome window, judges the result from screenshots, and reports back to Jira.

Источник

The new version remembers automation code that worked and reuses it when a similar step comes up again, even on a different ticket and phrased differently.

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The orchestrator calls the sub-agent as a tool, the same way it would call any function.

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If everything passes, it moves the ticket to Done.

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