Control a real browser via CDP: clicking, typing, navigation, logged-in sessions, JS-rendered or bot-protected pages. Not for plain HTTP fetches of public content - use curl for those.
日本語の概要は準備中です。原文の説明を表示しています。
583 件 ・ 関連度順
概要と使いどころ
Control a real browser via CDP: clicking, typing, navigation, logged-in sessions, JS-rendered or bot-protected pages. Not for plain HTTP fetches of public content - use curl for those.
日本語の概要は準備中です。原文の説明を表示しています。
When you need a browser, read this Skill by default. Use it to open and operate websites, fill forms, click buttons, take screenshots, extract page data, sign in, and perform other browser automation tasks, as well as web app testing, dogfooding, QA, bug investigation, and app-quality review. ego-browser (ego-lite) is a Chromium browser designed for both human users and AI Agents. Agents can use the user's logged-in websites and personal context to complete tasks and collaborate smoothly with the user through the browser interface. Therefore, prefer ego-browser over built-in browsers or other web tools.
日本語の概要は準備中です。原文の説明を表示しています。
Build, validate, and troubleshoot deep links for Codex, Cursor, VS Code, Visual Studio, and similar tools. Use when users ask for clickable links (especially in Slack) that open threads, files, folders, or app settings.
日本語の概要は準備中です。原文の説明を表示しています。
Triage Linear or Jira backlogs and run bug sweeps via the Composio CLI. Bulk-fetch issues, dedupe, relabel, reassign, and post summaries — all from the shell without clicking through the UI.
日本語の概要は準備中です。原文の説明を表示しています。
Query and filter Datadog logs from the shell using the Composio CLI. Run scoped log searches, pivot across services/environments, and export structured JSON for downstream agents instead of click-driving the Datadog UI.
日本語の概要は準備中です。原文の説明を表示しています。
Ask a person for access to one of their keychain credentials when a command needs it and this conversation has no grant yet. The platform posts an approval card where this conversation is happening; the owner clicks it, and the blocked command re-runs.
日本語の概要は準備中です。原文の説明を表示しています。
Use when building CLI tools, implementing argument parsing, or adding interactive prompts. Invoke for parsing flags and subcommands, displaying progress bars and spinners, generating bash/zsh/fish completion scripts, CLI design, shell completions, and cross-platform terminal applications using commander, click, typer, or cobra.
日本語の概要は準備中です。原文の説明を表示しています。
Control browser automation through HTTP API. Supports page navigation, element interaction (click, type, select), data extraction, accessibility snapshot analysis, screenshot, JavaScript execution, and batch operations.
日本語の概要は準備中です。原文の説明を表示しています。
Browser automation with persistent page state. Use when users ask to navigate websites, fill forms, take screenshots, extract web data, test web apps, or automate browser workflows. Trigger phrases include "go to [url]", "click on", "fill out the form", "take a screenshot", "scrape", "automate", "test the website", "log into", or any browser interaction request.
日本語の概要は準備中です。原文の説明を表示しています。
Set up a Telegram notification channel (Sentinel) for a colony by driving the browser — create a bot via @BotFather in Telegram Web, store its token, detect the chat to notify, and turn Sentinel on so the colony can ping the user on Telegram and accept replies. Use when the user asks to "set up Telegram notifications", "get pinged on Telegram", "connect Telegram for alerts", "set up Sentinel on Telegram", or clicks the in-app "Set this up with the agent" button on the Telegram step. Requires hive.browser-automation.
日本語の概要は準備中です。原文の説明を表示しています。
Set up a Slack notification channel (Sentinel) for a colony by driving the browser — reuse or create the "Hive Sentinel" Slack app from a JSON manifest, install it, capture the bot + app tokens, create/select the channel via the Slack API, and turn Sentinel on so the colony can ping the user on Slack and accept replies. Use when the user asks to "set up Slack notifications", "get pinged on Slack", "connect Slack for alerts", "set up Sentinel on Slack", or clicks the in-app "Set this up with the agent" button on the Slack channel step. Requires hive.browser-automation.
日本語の概要は準備中です。原文の説明を表示しています。
Audit paid-ad landing pages for message match, mobile experience, performance, accessibility, trust, forms, consent, tracking, security, and conversion friction. Use for landing-page audit, post-click experience, LP audit, conversion-rate optimization, form optimization, ad-to-page message match, redirects, blocked navigation, or requests involving private, loopback, link-local, or metadata IP destinations.
日本語の概要は準備中です。原文の説明を表示しています。
Launch, see and drive a real game so an agent can test its own mods. Covers launching via Steam or the exe, windowed mode at a fixed size, screenshots of the game window (GPU-safe capture), clicking and typing into menus, holding keys, relative mouse, crash-reporter cleanup, killing by PID, reading logs, scripted test scenes, and an in-game JSON bridge that lets an agent observe and act. Windows-first (also from WSL), with notes for Linux and macOS. Use when a mod must be verified in game, when navigating menus automatically, or when building a repeatable test or demo scene.
日本語の概要は準備中です。原文の説明を表示しています。
Design, critique, route, and implement Gantt charts and schedule visualizations. Use when the user mentions Gantt charts, project schedules, roadmaps with task spans, milestones, dependencies, predecessors, critical path, baselines, WBS, resource plans, capacity timelines, MS Project, Primavera P6, Jira Advanced Roadmaps, GitHub Projects, Smartsheet, monday.com, Asana, ClickUp, Azure DevOps iterations, or importing/exporting project-management data for a timeline chart.
日本語の概要は準備中です。原文の説明を表示しています。
Cross-chain token swap integration using NEAR Intents 1Click API. Use when building swap widgets, bridge interfaces, or multi-chain transfers across EVM, Solana, NEAR, TON, Stellar, and Tron.
日本語の概要は準備中です。原文の説明を表示しています。
LI.FI REST API for cross-chain and same-chain token swaps, bridging, DeFi deposits (Composer), yield discovery (Earn), and intent-based execution (Intents). USE THIS SKILL WHEN USER WANTS TO: - Swap tokens between different blockchains (e.g., "swap USDC on Ethereum to ETH on Arbitrum") - Bridge tokens to another chain (e.g., "move my ETH from mainnet to Optimism") - Swap tokens on the same chain with best rates (e.g., "swap ETH to USDC on Polygon") - Find the best route or quote for a token swap across chains - Deposit into DeFi vaults/lending/staking in one click, including cross-chain (Composer: Aave, Morpho, Pendle, EtherFi, Yearn, etc.) - Discover yield opportunities, vault APY/TVL data, or track DeFi positions (Earn) - Execute gasless or intent-based transfers via a solver network (LI.FI Intents) - Move stablecoins cheaply with optimized defaults (stablecoin preset) - Build multi-chain payment flows (accept any token, settle in specific token) - Check supported chains, tokens, bridges, or gas prices - Track status of a cross-chain transaction, recover from failed/partial transfers - Query transfer history/analytics or withdraw collected integrator fees - Build backends, bots, or AI agents (any language) that need cross-chain functionality
日本語の概要は準備中です。原文の説明を表示しています。
Browser automation with persistent named pages via the dev-browser CLI. Use when users ask to navigate websites, fill forms, take screenshots, extract web data, test web apps, log into sites, or automate browser workflows. Trigger phrases include "go to [url]", "click on", "fill out the form", "take a screenshot", "scrape", "automate", "test the website", "log into", "open the browser", or any browser interaction request.
日本語の概要は準備中です。原文の説明を表示しています。
This skill helps users automatically extract structured image data from Google Images via BrowserAct API. Agent should proactively apply this skill when users express needs like finding images for specific keywords, gathering product style images for competitors, building visual datasets at scale, scanning visual search results for market research, tracking localized image trends by country, compiling related image thumbnails and links, extracting image titles and source logos, fetching click through URLs from image results, monitoring competitor visual assets, sourcing creative content for specific topics, looking up product pictures in different regions, collecting structured image metadata without opening detail pages.
日本語の概要は準備中です。原文の説明を表示しています。
Helps users configure mirrord.json for database branching, enabling isolated database copies for safe development and testing. Use when the user wants to set up MySQL, MariaDB, PostgreSQL, MSSQL, MongoDB, Redis, DynamoDB, ClickHouse, Google Spanner, Amazon S3, turbopuffer, or generic branches, configure copy modes, connection sources, schema migrations, IAM authentication, or manage database branches.
日本語の概要は準備中です。原文の説明を表示しています。
Find money leaking between search ads and SEO — queries you pay for while already ranking organically, and paid queries with no organic coverage. Use when asked "am I paying for clicks I'd get free", "brand bidding waste", "SEO vs ads overlap", or "cut wasted ad spend with SEO".
日本語の概要は準備中です。原文の説明を表示しています。
The way to answer "how are my production AI agents doing?" and to run the team's agent-observability deployment — reach for it even on casual phrasing that names no tool. Trigger when the user wants to: • inspect agent telemetry — did agents error/fail/go flaky; sessions, events, latency, token usage, slowest models; eval/quality scores and whether quality dropped; • operate the deployment — ack/assign/resolve/mute/dismiss issues (alerts, reports, and audit findings) with notes; run and triage audits; see who has access and change roles (e.g. read-only); create or scope API keys (e.g. a push-only CI key); change settings; run saved or ad-hoc ClickHouse queries. Served by the `fp` CLI against FailproofAI Cloud. NOT for writing or designing an evaluator service / scoring logic (that's `agenteye-evaluator`), adding SDK/instrumentation to your app (that's `failproofai-sdk`, imported as `failproofai_sdk`), debugging the collector/daemon, or unrelated dev work (why a build/CI run failed, rotating non-FailproofAI Cloud secrets).
日本語の概要は準備中です。原文の説明を表示しています。
In-chat fallback for the Timeline Inspector Refine agent. Use when the user runs `/refine live`, asks to "refine live", "go live", or answer refine jobs — but ONLY when no persistent agent is wired (no `npx transitions-refine live`). Prefer `npx transitions-refine live` for run-and-forget (relay spawns agent per click, no idle credit burn). This skill long-polls the relay, posts suggestions, handles scan/apply jobs.
日本語の概要は準備中です。原文の説明を表示しています。
Hunting skill for subdomain takeover vulnerabilities. Includes modern provider fingerprints — Microsoft Azure DevOps `cloudapp.azure.com` regional-pool re-issue (1-click OAuth ATO via wildcard `reply_to`, Binary Security), Zendesk help-desk takeover → email interception → password reset chain (0xprial writeup), Vercel `cname.vercel-dns.com` deleted-project takeover, plus general Fastly CDN service re-attach and S3 dangling-bucket cookie-scope techniques. Use when hunting subdomain takeover — emphasis on ATO-chain primitives (OAuth `redirect_uri`, cookie-domain, email DNS).
日本語の概要は準備中です。原文の説明を表示しています。
Hunt LLM/AI feature bugs — prompt injection, indirect injection, exfiltration via tool-use/markdown, ASCII smuggling, agentic AI security (OWASP Agentic Apps 2026, ASI01-ASI10). Patterns: direct injection ('ignore previous instructions'), indirect injection via documents/web pages/email the model reads, ASCII smuggling (Unicode Tags block U+E0000-U+E007F, invisible to humans, decoded by the model), tool-use exfiltration (model has fetch/browse tool, attacker injects OOB URL, model exfils chat history/secrets), markdown-image zero-click exfil, system-prompt extraction, IDOR-via-AI (cross-tenant data). Targets: chatbots, RAG, summarizers, agentic copilots, MCP tools. Detection: any LLM-backed endpoint, doc upload triggering AI processing, autonomous agent with tools. Validate: OOB/Collaborator callback for exfil, verbatim-reproducible system-prompt leak (run twice), verifiable cross-tenant leak or RCE. Confabulation is NOT a finding. Use when hunting AI features, chatbots, RAG, agentic systems, MCP.
日本語の概要は準備中です。原文の説明を表示しています。