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What you can do with Deer Workflow

deer-workflow is an open-source TypeScript runtime for building observable, reusable Agent graphs, where code defines the steps and Coding Agents do the work inside each step.

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deerwork-ai/deer-workflow on GitHub

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What do you want to do?

5 use cases

  • Generate a runnable TypeScript workflow from plain English

    Describe a multi-step job in one sentence and get a runnable TypeScript workflow module.

    View prompt
    Using the deer-workflow repository (deerwork-ai/deer-workflow), generate a runnable TypeScript Workflow for <target job description> with the deer-workflow create command, save it to workflow.ts, and run it with a sample input. Expected output: a workflow.ts file plus a run result. Verify that the run finishes and that the phases in the file match the steps described in the job.

  • Run a workflow in CI and parse its JSON event stream

    Execute a saved workflow in a build pipeline and read a stable JSONL event stream.

    View prompt
    Using the deer-workflow repository (deerwork-ai/deer-workflow), add a CI step that runs ./workflow.ts with the input <target input JSON> and the --print flag. Expected output: a captured JSONL event stream saved as an artifact. Verify that every stdout line parses as JSON before the job reports success.

  • Run the Deep Research example to produce an HTML report

    Clone the repo and run a bundled example that researches angles in parallel and builds a report.

    View prompt
    Using the deer-workflow repository (deerwork-ai/deer-workflow), follow examples/deep-research/README.md to run the Deep Research example on the topic <target topic>. Expected output: an interactive HTML report. Verify that the report includes the claims verification step described in the example README.

  • Generate a workflow with Claude Code or Pi instead of Codex

    Switch the Agent runtime used to generate a workflow without changing the rest of the process.

    View prompt
    Using the deer-workflow repository (deerwork-ai/deer-workflow), generate a Workflow for <target job description> with the --agent claude option and save it to workflow.ts. Expected output: a runnable TypeScript module. Verify that the file runs with a sample input and that the phases match the job.

  • Add an integration for a new coding agent

    Clone the repo, run the checks, and build a new Agent integration beside the built-in ones.

    View prompt
    Using the deer-workflow repository (deerwork-ai/deer-workflow), read the public Agent interface and the ClaudeAgent and PiAgent integrations, then draft a new Agent integration for <target coding agent>. Expected output: a pull request branch with the new integration. Verify that bun run check passes before you report the work as done.

How to use Deer Workflow

  1. Check you have what it needs: Bun installed (https://bun.sh); Codex CLI installed and signed in, since Codex is the default Agent runtime; A terminal on macOS, Linux, or Windows with Bun support.
  2. Open deerwork-ai/deer-workflow on GitHub and read the README and license.
  3. Install the released CLI with bun install --global @deerwork-ai/deer-workflow.
  4. Make sure you are signed in to Codex CLI, which is the default Agent runtime.
  5. Generate the module with deer-workflow create "Create a Workflow that accepts a topics string array, researches each topic in parallel, and synthesizes a report" > workflow.ts. (inferred, check the README)
  6. Run it with its example input: deer-workflow run ./workflow.ts --input '{"topics":["Agent Skills","Dynamic Workflows"]}'. (inferred, check the README)

These steps come from our top use case, Generate a runnable TypeScript workflow from plain English, which also has a copy-paste agent prompt.

Deer Workflow alternatives · Best AI repos for Software and DevOps

About this repo

Requirements

  • Bun installed (https://bun.sh)
  • Codex CLI installed and signed in, since Codex is the default Agent runtime
  • A terminal on macOS, Linux, or Windows with Bun support
  • Git, if you plan to clone the repository for examples or development
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Questions about Deer Workflow

What is Deer Workflow?

deer-workflow is an open-source TypeScript runtime for building observable, reusable Agent graphs, where code defines the steps and Coding Agents do the work inside each step. It is an open-source project on GitHub: https://github.com/deerwork-ai/deer-workflow.

Who is Deer Workflow for?

Written for developers and engineering teams who want repeatable multi-step AI agent jobs that they can read, review, and run from a terminal or CI.

What can I do with Deer Workflow?

5 use cases so far, for example: Generate a runnable TypeScript workflow from plain English; Run a workflow in CI and parse its JSON event stream; Run the Deep Research example to produce an HTML report. Each has steps and a copy-paste agent prompt.

What do I need to run Deer Workflow?

Bun installed (https://bun.sh); Codex CLI installed and signed in, since Codex is the default Agent runtime; A terminal on macOS, Linux, or Windows with Bun support; Git, if you plan to clone the repository for examples or development.

What are alternatives to Deer Workflow?

Other hot AI repos in Software and DevOps: Harness2, iFixAi, Orca, Diagram Design, AI Memory.

Is Deer Workflow safe to run?

Deduped does not own, audit or vouch for it. Read the README and license, run it on your own systems first and review every command before you run it.