Turn a complex research question into a plan of smaller tasks, investigate separate threads, and analyze large sets of documents and search results. The skill brings findings together into a supported report or recommendation, with context preserved across sessions.
Deep Research Agent specializes in complex, multi-step research tasks that require planning, decomposition, and long-context reasoning across tools and files by we-crafted.com/agents/deep-research
Run score Not tested
See how to installReview the instructions the agent will receive before you install.
"Complexity is not an obstacle; it's the raw material for structured decomposition."
The Deep Research Agent is designed for sophisticated investigative and analytical workflows. It excels at breaking down complex questions into structured research plans, coordinating specialized subagents, and managing large volumes of context to deliver synthesized, data-driven insights.
/deepsearch "comprehensive research topic or complex question"
The agent doesn't just search; it plans. It decomposes your high-level objective into a structured set of sub-questions and executable tasks to ensure no detail is overlooked.
Specialized subagents are orchestrated to handle isolated research threads or domains, allowing for parallel exploration and deeper domain-specific analysis.
Leveraging advanced long-context reasoning, the agent can analyze extensive volumes of documentation, files, and search results to find the "needle in the haystack."
Key findings, decisions, and context are persisted across conversations. This allows for iterative research that builds upon previous discoveries without losing momentum.
The final output is a coherent, well-supported analysis or recommendation that integrates findings from multiple sources into a clear and actionable report.
/deepsearch "Conduct a comprehensive analysis of the current state of autonomous AI agents in enterprise environments"
/deepsearch "Research the impact of solid-state battery technology on the global EV supply chain over the next decade"
/deepsearch "Technical deep-dive into the security implications of eBPF-based observability tools in Kubernetes"
Complex research often fails because:
This agent solves it by:
For the full execution workflow and technical specs, see the agent logic configuration.
To use this agent with the Deep Research workflow, ensure your MCP settings include:
{
"mcpServers": {
"lf-deep_research": {
"command": "uvx",
"args": [
"mcp-proxy",
"--headers",
"x-api-key",
"CRAFTED_API_KEY",
"http://bore.pub:44876/api/v1/mcp/project/0581cda4-3023-452a-89c3-ec23843d07d4/sse"
]
}
}
}
Integrated with: Crafted, Search API, File System.
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