Automate browser tasks with agent-browser, using snapshots that label page elements for the agent. Handle login flows, fill and submit forms, extract page information, and capture screenshots through a repeatable navigation and interaction workflow.
中文简介正在准备中。当前显示英语简介。
Web browser automation with AI-optimized snapshots for claude-flow agents
安装前可以查看交给 AI 代理的指令内容。
Web browser automation using agent-browser with AI-optimized snapshots. Reduces context by 93% using element refs (@e1, @e2) instead of full DOM.
# 1. Navigate to page
agent-browser open <url>
# 2. Get accessibility tree with element refs
agent-browser snapshot -i # -i = interactive elements only
# 3. Interact using refs from snapshot
agent-browser click @e2
agent-browser fill @e3 "text"
# 4. Re-snapshot after page changes
agent-browser snapshot -i
| Command | Description |
|---|---|
open <url> | Navigate to URL |
back | Go back |
forward | Go forward |
reload | Reload page |
close | Close browser |
| Command | Description |
|---|---|
snapshot | Full accessibility tree |
snapshot -i | Interactive elements only (buttons, links, inputs) |
snapshot -c | Compact (remove empty elements) |
snapshot -d 3 | Limit depth to 3 levels |
screenshot [path] | Capture screenshot (base64 if no path) |
| Command | Description |
|---|---|
click <sel> | Click element |
fill <sel> <text> | Clear and fill input |
type <sel> <text> | Type with key events |
press <key> | Press key (Enter, Tab, etc.) |
hover <sel> | Hover element |
select <sel> <val> | Select dropdown option |
check/uncheck <sel> | Toggle checkbox |
scroll <dir> [px] | Scroll page |
| Command | Description |
|---|---|
get text <sel> | Get text content |
get html <sel> | Get innerHTML |
get value <sel> | Get input value |
get attr <sel> <attr> | Get attribute |
get title | Get page title |
get url | Get current URL |
| Command | Description |
|---|---|
wait <selector> | Wait for element |
wait <ms> | Wait milliseconds |
wait --text "text" | Wait for text |
wait --url "pattern" | Wait for URL |
wait --load networkidle | Wait for load state |
| Command | Description |
|---|---|
--session <name> | Use isolated session |
session list | List active sessions |
# Get refs from snapshot
agent-browser snapshot -i
# Output: button "Submit" [ref=e2]
# Use ref to interact
agent-browser click @e2
agent-browser click "#submit"
agent-browser fill ".email-input" "test@test.com"
agent-browser find role button click --name "Submit"
agent-browser find label "Email" fill "test@test.com"
agent-browser find testid "login-btn" click
agent-browser open https://example.com/login
agent-browser snapshot -i
agent-browser fill @e2 "user@example.com"
agent-browser fill @e3 "password123"
agent-browser click @e4
agent-browser wait --url "**/dashboard"
agent-browser open https://example.com/contact
agent-browser snapshot -i
agent-browser fill @e1 "John Doe"
agent-browser fill @e2 "john@example.com"
agent-browser fill @e3 "Hello, this is my message"
agent-browser click @e4
agent-browser wait --text "Thank you"
agent-browser open https://example.com/products
agent-browser snapshot -i
# Iterate through product refs
agent-browser get text @e1 # Product name
agent-browser get text @e2 # Price
agent-browser get attr @e3 href # Link
# Session 1: Navigator
agent-browser --session nav open https://example.com
agent-browser --session nav state save auth.json
# Session 2: Scraper (uses same auth)
agent-browser --session scrape state load auth.json
agent-browser --session scrape open https://example.com/data
agent-browser --session scrape snapshot -i
All browser operations are available as MCP tools with browser/ prefix:
browser/openbrowser/snapshotbrowser/clickbrowser/fillbrowser/screenshot# Store successful patterns
npx @claude-flow/cli memory store --namespace browser-patterns --key "login-flow" --value "snapshot->fill->click->wait"
# Retrieve before similar task
npx @claude-flow/cli memory search --query "login automation"
# Pre-browse hook (get context)
npx @claude-flow/cli hooks pre-edit --file "browser-task.ts"
# Post-browse hook (record success)
npx @claude-flow/cli hooks post-task --task-id "browse-1" --success true
-i flag - Gets only interactive elements, smaller output还没有评价。欢迎分享你的使用感受。
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Build advanced AgentDB workflows with database synchronization, multiple databases, and search that combines meaning with attribute filters. Covers similarity measures, diverse search results, and operational patterns for distributed AI applications.
中文简介正在准备中。当前显示英语简介。
Create AgentDB learning plugins that use recorded experience to improve agent decisions. Choose a learning method, store states, actions, and rewards, train models, and evaluate suggested actions through CLI and API workflows.
中文简介正在准备中。当前显示英语简介。
Build AI agents that retain conversation history, user preferences, and useful interaction patterns with AgentDB. The skill covers persistent storage, meaning memories survive between sessions, plus retrieval, context management, and ReasoningBank integration.
中文简介正在准备中。当前显示英语简介。
Tune AgentDB memory use and search speed through quantization, which stores vectors more compactly, search indexes, caching, and batch operations. Includes configuration examples and benchmarks to help balance accuracy, speed, and storage as datasets grow.
中文简介正在准备中。当前显示英语简介。
Build document search with AgentDB that finds related content by meaning. Store documents as numerical representations, combine similarity search with metadata filters, and retrieve relevant passages for systems that generate answers using source material.
中文简介正在准备中。当前显示英语简介。
Build a room-specific sensing model by recording an empty room and occupants performing activities, then training small specialized models. The workflow continues into live monitoring of presence, posture, and breathing in the calibrated room.
中文简介正在准备中。当前显示英语简介。