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jeremylongshore
jeremylongshoreCOMMUNITY
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deer_flow

Automate research, code generation, and artifact creation for any topic.

2|Updated Mar 17, 2026
Search Tags:#automation#workflow#research#artifact#specialist#code-generation#deer-flow
One-click install
npx skills add https://github.com/jeremylongshore/oss-agent-lab --skill deer-flow
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: deer_flow
Source: https://github.com/jeremylongshore/oss-agent-lab/tree/main/agents/specialists/deer_flow
Command: npx skills add https://github.com/jeremylongshore/oss-agent-lab --skill deer-flow

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Deer Flow wraps end-to-end research, code generation, and artifact packaging into a single, composable OSS Agent Lab specialist, reducing handoffs and time-to-deliverable.

Core Features & Use Cases

  • research: Gather findings, sources, and a summary with a confidence score for any topic.
  • code_generation: Produce an implementation, tests, and explanation from a natural-language specification.
  • creation: Package outputs into a versioned artifact with creation metadata.
  • summarize: Provide concise summaries suitable for downstream prompting. Quickly transform a research topic into a runnable artifact ready for deployment.

Quick Start

Provide a topic to trigger the full deer_flow pipeline: research, code generation, and artifact creation.

Frequently Asked Questions about deer_flow

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate research, code generation, and artifact creation end-to-end?▼

End-to-end research, code generation, and artifact creation automation wraps these stages into a single pipeline, transforming a research topic into a runnable artifact with research findings, implementation code, and versioned packaging.

Can I generate code and tests from a natural language specification automatically?▼

Code generation from a natural language specification automatically produces an implementation, tests, and explanation, enabling rapid implementation when you provide a topic or specification to trigger the pipeline.

Does this research and code generation workflow support multiple output formats like Python API and CLI?▼

The research and code generation workflow supports multiple output formats including Python API, CLI, MCP Server, Agent Skill, and REST API, allowing flexible integration into software engineering workflows.

What is the best way to package code generation outputs into a versioned artifact?▼

Packaging code generation outputs into a versioned artifact uses the creation feature, which bundles implementation, tests, and research findings with creation metadata for deployment-ready deliverables.

Do I need external dependencies to run the research and artifact automation pipeline?▼

No external dependencies are required to run the research and artifact automation pipeline, as the specialist operates independently for multi-stage orchestration, tool integration, and deliverable packaging.

How does the research stage handle confidence scoring for gathered findings?▼

The research stage gathers findings, sources, and a summary with a confidence score for any given topic, providing concise summaries suitable for downstream prompting and rapid exploration.

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