// Browser automation via Playwriter (remorses) using persistent Chrome sessions and the full Playwright Page API.
| name | playwriter |
| description | Browser automation via Playwriter (remorses) using persistent Chrome sessions and the full Playwright Page API. |
| hats | ["developer","qa_tester"] |
| metadata | {"internal":true} |
Use Playwriter to run Playwright Page scripts against your local Chrome session. This preserves logins, cookies, and extensions, which is ideal for web dashboard testing and authenticated flows.
npm i -g playwriter
playwriter session new
playwriter session list
playwriter -s <session_id> -e "await page.goto('https://example.com')"
Within -e, these are available in scope:
page (Playwright Page)context (BrowserContext)state (persistent object across calls in the same session)require (for loading helper modules)Example state persistence:
playwriter -s <session_id> -e "state.lastUrl = page.url()"
playwriter -s <session_id> -e "console.log(state.lastUrl)"
playwriter -s <session_id> -e "await page.goto('http://localhost:3000'); await page.getByRole('button', { name: 'Run' }).click();"
playwriter -s <session_id> -e "await page.getByLabel('Email').fill('qa@example.com'); await page.getByLabel('Password').fill('secret'); await page.getByRole('button', { name: 'Sign in' }).click();"
playwriter -s <session_id> -e "const { screenshotWithAccessibilityLabels } = require('playwriter'); await screenshotWithAccessibilityLabels(page, { path: '/tmp/a11y.png' });"
playwriter -s <session_id> -e "await page.route('**/api/**', async route => { const res = await route.fetch(); const body = await res.json(); await route.fulfill({ json: { ...body, injected: true } }); });"
playwriter -s <session_id> -e "const text = await page.locator('main').innerText(); console.log(text);"
getByRole and getByLabel for stable selectors.state.Introspect, explain, and improve Ralph Orchestrator using its published llms.txt doc map. Use this skill whenever the user asks questions about Ralph's behavior, wants to understand how a Ralph internal works (event loop, hats, memories, tasks, backends, presets), debug an unfamiliar failure mode, or propose a code change to the ralph-orchestrator repo. The skill teaches the agent to discover authoritative answers from the live docs via llms.txt before guessing, and to scope improvements through the published architecture rather than the local checkout alone.
Run, monitor, resume, merge, and debug Ralph loops. Use this skill whenever the user asks to operate `ralph run` or `ralph loops`, inspect loop state, recover suspended loops, analyze diagnostics, or unblock merge queue issues.
Guides implementation of code tasks using test-driven development in an Explore, Plan, Code, Commit workflow. Acts as a Technical Implementation Partner and TDD Coach — following existing patterns, avoiding over-engineering, and producing idiomatic, modern code.
Generates structured .code-task.md files from descriptions or PDD implementation plans. Auto-detects input type, creates properly formatted tasks with Given-When-Then acceptance criteria.
Use when testing Ralph's hat collection presets, validating preset configurations, or auditing the preset library for bugs and UX issues.
Lists all code tasks in the repository with their status, dates, and metadata. Useful for getting an overview of pending work or finding specific tasks.