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Persistent memory system for AI agents following Model Context Protocol (MCP). Use for storing long-term memories across sessions, semantic search of past knowledge, building knowledge graphs, auto-injecting context, deduplicating memories, syncing to cloud storage. Essential for agents that need to remember decisions, solutions, preferences, and learned patterns over time.
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| name | cuecue-deep-research |
| description | Conduct deep financial research using CueCue's AI-powered multi-agent system |
| version | 1.0.3 |
| author | CueCue Team |
| keywords | ["research","financial-analysis","ai-agents","report-generation","data-analysis","imitation-writing"] |
| metadata | {"clawdbot":{"emoji":"🔭","requires":{"env":["CUECUE_API_KEY"]},"primaryEnv":"CUECUE_API_KEY"}} |
Execute comprehensive financial research queries using CueCue's multi-agent AI system. This TypeScript implementation provides the same functionality as the Python version with modern async/await patterns and full type safety.
CueCue Deep Research orchestrates multiple AI agents to:
The skill filters the verbose agent workflow to show only:
⏱️ Execution Time: Depending on the complexity of your research question, the process may take 5-30 minutes. The system performs comprehensive research including web crawling, data analysis, and report generation. Please be patient and wait for the complete results.
Important: When using this skill, you MUST monitor the research progress by checking the command output:
Progress Monitoring: The research process outputs progress information in real-time. You should check the output every 5 minutes to:
Progress URL: The command will output a URL like "Research begin. You can view progress at: https://cuecue.cn/c/..." - this URL is for human users to view the web interface, NOT for you to fetch. You should monitor progress through the command's stdout output.
User Communication: Keep the user informed about:
Timeout Handling: If the command appears to hang or timeout, inform the user that the research may still be processing on the server, and they can check the web interface URL.
User-Facing Communication Style: When informing users about progress monitoring:
Why: Users care about what you'll do, not how you do it. Keep communication focused on outcomes and user value, not internal plumbing.
Since AI assistants cannot actively "loop and check" on their own, use OpenClaw's cron system to automate progress monitoring.
Recommended Approach: Use Isolated Session
Using sessionTarget: "isolated" with payload.kind: "agentTurn" is the most reliable way to get progress updates delivered directly to the chat channel.
Step 1: Start research in background
// Start the research task
exec({
command: "cuecue-research 'Your research query' --output ~/clawd/cuecue-reports/2026-02-01-10-00-research.md",
background: true
})
// Returns: { sessionId: "wild-river", pid: 12345 }
Step 2: Create a cron job to monitor progress
cron.add({
name: "Monitor CueCue Research: wild-river",
schedule: {
kind: "every",
everyMs: 300000 // 5 minutes
},
sessionTarget: "isolated",
wakeMode: "now", // IMPORTANT: Use "now" to trigger immediately
payload: {
kind: "agentTurn",
message: "检查 CueCue 研究进度 (session: wild-river)。使用 process log wild-river 检查输出。如果看到 '✅ Research complete',则:1) 读取报告文件并总结关键发现;2) 使用 cron.remove 删除此监控任务。如果仍在运行,汇报最新的 📋 Task 进度。",
deliver: true,
channel: "feishu", // or "telegram", "discord", etc.
to: "GROUP_ID_OR_CHAT_ID" // The channel where the research was requested
}
})
// Returns: { id: "abc-123-def", ... }
Important Configuration:
sessionTarget: "isolated" - Creates an isolated sub-agent sessionpayload.kind: "agentTurn" - Runs the agent and delivers the responsedeliver: true - Ensures the response is sent to the chatchannel - Specify the messaging platform (feishu, telegram, discord, etc.)to - The target chat/group ID where updates should be sentwakeMode: "now" - Triggers immediately without waiting for heartbeatStep 3: Cron will automatically check every 5 minutes
The cron job will:
process log wild-river for new outputStep 4: Manual cleanup (if needed)
If the research fails or you need to stop monitoring:
// List all cron jobs
cron.list()
// Remove the monitoring job
cron.remove({ jobId: "abc-123-def" })
Complete Example Workflow:
// 1. Start research
const result = exec({
command: "cuecue-research '2026年金银价格分析' --output ~/clawd/cuecue-reports/2026-02-01-gold-analysis.md",
background: true
})
const sessionId = result.sessionId // e.g., "wild-river"
// 2. Get current channel info (from runtime context)
const channel = "feishu" // Current channel
const chatId = "oc_abac3e3037a0726ef4b4aa330d5ed590" // Current group/chat ID
// 3. Create monitoring cron
const cronJob = cron.add({
name: `Monitor CueCue: ${sessionId}`,
schedule: { kind: "every", everyMs: 300000 },
sessionTarget: "isolated",
wakeMode: "now",
payload: {
kind: "agentTurn",
message: `检查研究进度 (session: ${sessionId})。完成后读取报告并总结,然后删除此 cron。`,
deliver: true,
channel: channel,
to: chatId
}
})
// 4. Inform user (user-friendly, no technical details)
reply(`🔭 研究已启动!
📊 进度追踪: https://cuecue.cn/c/...
⏰ 我会每 5 分钟自动检查进度并汇报
`)
// 5. Cron handles the rest automatically
// The isolated session will:
Troubleshooting:
If you don't receive progress updates:
cron.list() to verify the job is running (lastStatus: "ok")wakeMode: "now" is set (not "next-heartbeat")deliver: true and correct channel + to valuescron.runs({ jobId }) for execution history and errorsAlternative: Main Session (Not Recommended)
If you prefer to use sessionTarget: "main" with payload.kind: "systemEvent", note that:
HEARTBEAT.md contains non-comment content to avoid empty-heartbeat-file errorsNote: The cron payload should include logic to delete itself. Use cron.remove({ jobId: "<job-id>" }) when the research completes.
The skill requires a CueCue API key to function. You can configure it in two ways:
Set the API key in your OpenClaw configuration using the CLI:
# One-line command to set the API key(openclaw command may be clawdbot or moltbot)
openclaw config set skills.entries.cuecue-deep-research.env.CUECUE_API_KEY "your-api-key-here"
This will:
~/.openclaw/openclaw.json under skills.entries.cuecue-deep-research.envTo verify the configuration:
openclaw config get skills.entries.cuecue-deep-research.env.CUECUE_API_KEY
then restart the gateway
openclaw gateway restart
You can also pass the API key directly when running the command:
cuecue-research "Your query" --api-key YOUR_API_KEY
Note: The OpenClaw config method is recommended because:
# Install globally
npm install -g cuecue-deep-research@1.0.3
# Or install locally in your project
npm install cuecue-deep-research@1.0.3
# Using environment variable (recommended)
cuecue-research "Tesla Q3 2024 revenue analysis"
# Or specify API key directly
cuecue-research "Tesla Q3 2024 revenue analysis" --api-key YOUR_API_KEY
cuecue-research "BYD vs Tesla market comparison" --output ~/clawd/cuecue-reports/2026-01-30-14-30-byd-tesla-comparison.md
Note: The output path should use the format ~/clawd/cuecue-reports/YYYY-MM-DD-HH-MM-descriptive-name.md where the timestamp represents when the research was initiated. The ~ will be expanded to your home directory.
cuecue-research "Analyze CATL competitive advantages" \
--output ~/clawd/cuecue-reports/2026-01-30-11-20-catl-analysis.md \
--template-id TEMPLATE_ID
cuecue-research "Further analyze supply chain risks" \
--output ~/clawd/cuecue-reports/2026-01-30-15-45-supply-chain-risks.md \
--conversation-id EXISTING_CONV_ID
cuecue-research "Electric vehicle market analysis" \
--output ~/clawd/cuecue-reports/2026-01-30-16-00-ev-market-analysis.md \
--mimic-url https://example.com/sample-article
The mimic feature analyzes the writing style, tone, and structure of the provided URL and applies it to the generated research report. This is useful for:
⚠️ Note: The --mimic-url and --template-id options cannot be used together. Choose one approach:
--template-id for predefined research frameworks (goal, search plan, report format)--mimic-url for style mimicking without a template| Option | Required | Description |
|---|---|---|
query | ✅ | Research question or topic |
--api-key | ❌ | Your CueCue API key (defaults to CUECUE_API_KEY env var) |
--base-url | ❌ | CueCue API base URL (defaults to CUECUE_BASE_URL env var or https://cuecue.cn) |
--conversation-id | ❌ | Continue an existing conversation |
--template-id | ❌ | Use a predefined research template (cannot be used with --mimic-url) |
--mimic-url | ❌ | URL to mimic the writing style from (cannot be used with --template-id) |
--output, -o | ❌ | Save report to file (markdown format). Recommended format: ~/clawd/cuecue-reports/clawd/cuecue-reports/YYYY-MM-DD-HH-MM-descriptive-name.md (e.g., ~/clawd/2026-01-30-12-41-tesla-analysis.md). The ~ will be expanded to your home directory. |
--verbose, -v | ❌ | Enable verbose logging |
--help, -h | ❌ | Show help message |
The skill provides real-time streaming output:
Starting Deep Research: Tesla Q3 2024 Financial Analysis
Check Progress: https://cuecue.cn/c/12345678-1234-1234-1234-123456789abc
📋 Task: Search for Tesla Q3 2024 financial data
📋 Task: Analyze revenue and profit trends
📝 Generating Report...
# Tesla Q3 2024 Financial Analysis
## Executive Summary
[Report content streams here in real-time...]
✅ Research complete
============================================================
📊 Research Summary
============================================================
Conversation ID: 12345678-1234-1234-1234-123456789abc
Tasks completed: 2
Report URL: https://cuecue.cn/c/12345678-1234-1234-1234-123456789abc
✅ Report saved to: ~/clawd/cuecue-reports/2026-01-30-10-15-tesla-q3-analysis.md
For issues or questions: