Use when manage multiple local CLI agents via tmux sessions (start/stop/monitor/assign) with cron-friendly scheduling.
中文简介正在准备中。当前显示原文说明。
To test local web applications, write native Python Playwright scripts.
中文简介正在准备中。当前显示原文说明。
安装前可以查看交给 AI 代理的指令内容。
To test local web applications, write native Python Playwright scripts.
Helper Scripts Available:
scripts/with_server.py - Manages server lifecycle (supports multiple servers)Always run scripts with --help first to see usage. DO NOT read the source until you try running the script first and find that a customized solution is abslutely necessary. These scripts can be very large and thus pollute your context window. They exist to be called directly as black-box scripts rather than ingested into your context window.
User task → Is it static HTML?
├─ Yes → Read HTML file directly to identify selectors
│ ├─ Success → Write Playwright script using selectors
│ └─ Fails/Incomplete → Treat as dynamic (below)
│
└─ No (dynamic webapp) → Is the server already running?
├─ No → Run: python scripts/with_server.py --help
│ Then use the helper + write simplified Playwright script
│
└─ Yes → Reconnaissance-then-action:
1. Navigate and wait for networkidle
2. Take screenshot or inspect DOM
3. Identify selectors from rendered state
4. Execute actions with discovered selectors
To start a server, run --help first, then use the helper:
Single server:
python scripts/with_server.py --server "npm run dev" --port 5173 -- python your_automation.py
Multiple servers (e.g., backend + frontend):
python scripts/with_server.py \
--server "cd backend && python server.py" --port 3000 \
--server "cd frontend && npm run dev" --port 5173 \
-- python your_automation.py
To create an automation script, include only Playwright logic (servers are managed automatically):
from playwright.sync_api import sync_playwright
with sync_playwright() as p:
browser = p.chromium.launch(headless=True) # Always launch chromium in headless mode
page = browser.new_page()
page.goto('http://localhost:5173') # Server already running and ready
page.wait_for_load_state('networkidle') # CRITICAL: Wait for JS to execute
# ... your automation logic
browser.close()
Inspect rendered DOM:
page.screenshot(path='/tmp/inspect.png', full_page=True)
content = page.content()
page.locator('button').all()
Identify selectors from inspection results
Execute actions using discovered selectors
❌ Don't inspect the DOM before waiting for networkidle on dynamic apps
✅ Do wait for page.wait_for_load_state('networkidle') before inspection
scripts/ can help. These scripts handle common, complex workflows reliably without cluttering the context window. Use --help to see usage, then invoke directly.sync_playwright() for synchronous scriptstext=, role=, CSS selectors, or IDspage.wait_for_selector() or page.wait_for_timeout()element_discovery.py - Discovering buttons, links, and inputs on a pagestatic_html_automation.py - Using file:// URLs for local HTMLconsole_logging.py - Capturing console logs during automationThis skill is applicable to execute the workflow or actions described in the overview.
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Use when manage multiple local CLI agents via tmux sessions (start/stop/monitor/assign) with cron-friendly scheduling.
中文简介正在准备中。当前显示原文说明。
Use when a hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).
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Reference for how BDB structures autonomous software engineering work — the seven-node dispatcher graph (Architect, TechLead, UI/UX, Engineering, Media/EventTech, Reviewer, Shipping) that /startcycle-graph actually runs. Use when you need the high-level lifecycle framing without inventing your own process.
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Tools are how AI agents interact with the world. A well-designed tool is the difference between an agent that works and one that hallucinates, fails silently, or costs 10x more tokens than necessary. This skill covers tool design from schema to error handling.
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Harness patterns for coding agents — memory, permissions, context engineering, delegation, skills, hooks, bootstrap.
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agenttrail: live map of a multi-agent build in the browser: which plan component is being worked on, by which agent or harness, what is done and what is stuck. Use when a multi-agent pipeline starts (/startcycle, /startcycle-graph, /teamwork-preview) or after a plan-canvas approve, when the user asks to see what the agents are doing ("live map", "build board", "who is running now"), or by yourself whenever a multi-agent run is under way — no user prompt needed.
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