The work experience layer for autonomous agents. Open-source core: https://github.com/ShuxinYang111/oysterworkflow-core
# Add to your Claude Code skills
git clone https://github.com/ShuxinYang111/oysterworkflowGuides for using ai agents skills like oysterworkflow.
Last scanned: 5/30/2026
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}oysterworkflow is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by ShuxinYang111. The work experience layer for autonomous agents. Open-source core: https://github.com/ShuxinYang111/oysterworkflow-core. It has 194 GitHub stars.
Yes. oysterworkflow passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.
Clone the repository with "git clone https://github.com/ShuxinYang111/oysterworkflow" and add it to your Claude Code skills directory (see the Installation section above).
Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh oysterworkflow against similar tools.
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The work experience layer for autonomous agents on macOS and Windows.
Website | Open Core | Download Latest Release | Release Notes | Report an Issue | Commercial Licensing
OysterWorkflow captures what humans and agents observe, how they react, and how they complete real work on computers. It turns screens, OCR text, clicks, keystrokes, retries, choices, and verification moves into reusable experience for AI agents.
The current release focuses on reviewable AI workflows: recording evidence, detecting candidate workflows, creating structured workflow graphs, and handing a pinned workflow revision to an agent. The Codex Plugin Beta lets Codex execute those workflows with its own apps and tools.
The core workflow pipeline is open source in OysterWorkflow Core under the Apache-2.0 license.
The open core includes the Screenpipe ingest client, OCR/UI/audio trace processing, event normalization, deduplication, segmentation, workflow discovery, OpenClaw skill extraction, and generated skill quality evaluation.
Autonomous agents need more than instructions. They need work experience.
Most real work is not just reasoning or a checklist. It is a compound of experience patterns: noticing, deciding, trying, fixing, verifying, and finishing. OysterWorkflow preserves those patterns from real computer work so agent stacks such as Codex, Claude Code, Cursor, OpenAI Agents, OpenClaw, and custom agents can reuse the path that already worked.
Skills are the first runtime artifact, not the final boundary of the product. Working on the harness and workflow script now.
The current release focuses on:
skill.json for the generated skill definitionassets.json for captured supporting evidencesummary.json for run and generation contextStart the recorder, do your work, and stop it. Here to review recorder metrics: screen states, OCR text, inputs, windows, and optional narration captured as evidence.

Review the work patterns OysterWorkflow detected from a noisy session, then choose the path worth turning into reusable agent experience.

Inspect generated steps and hints before installing the result to your agent.

Manage generated skills, copy the recommended execution prompt, and remove obsolete capabilities when they are no longer useful.

OysterWorkflow is most relevant if you:
The Codex Plugin Beta connects Codex to the OysterWorkflow Runtime running on the same Mac. OysterWorkflow provides workflow discovery, revision pinning, graph transitions, retry limits, and durable run state. Codex uses its own installed apps and tools to perform the real actions.
Requirements:
Install the marketplace and plugin:
codex plugin marketplace add ShuxinYang111/oysterworkflow
codex plugin add oysterworkflow@oysterworkflow
Then start a new Codex task and try:
Use OysterWorkflow to run “Screen sales inquiries and prepare replies”
This beta uses the local MCP endpoint at http://127.0.0.1:3034/api/codex/mcp, so OysterWorkflow must remain running while Codex uses the workflow.
Download the latest macOS or Windows build from Releases.
Current release assets:
OysterWorkflow-0.2.0-arm64.dmg in the latest releaseOysterWorkflow-Setup-0.1.0.exe in the v0.1.0 release; the Codex Plugin Beta is currently macOS-onlySHA-256:
macOS arm64 dmg:
8ff5f2c431f4815b61e1a975a07632d3769ae9b3398c072d8de254a5d930ade8
Windows x64 installer:
78dad16a0e9152173d128ca5c2674a4987c61a4245e5f67bd2650654687bf0cf
arm64)OysterWorkflow-0.2.0-arm64.dmg from the latest release..dmg and drag OysterWorkflow.app into Applications.Applications.Because OysterWorkflow records workflow evidence, macOS may ask for:
OysterWorkflow-Setup-0.1.0.exe from the latest release.Windows notes:
This public repository hosts release binaries, documentation, screenshots, issue tracking, and the official product website link. The private OysterWorkflow source code is not included here.
For the open-source implementation surface, see OysterWorkflow Core.
OysterWorkflow bundles third-party sidecar tools used by the recorder, including Screenpipe, FFmpeg, and ffprobe. These components keep their own license terms; they are not relicensed as OysterWorkflow code and are not covered by the PolyForm Noncommercial terms.
See THIRD-PARTY-NOTICES.md for bundled component notices, FFmpeg/ffprobe source information, and the build-time license profile recorded in screenpipe-bundle.json.
Which part of OysterWorkflow is open source?
OysterWorkflow Core is open source under Apache-2.0. It contains the CLI pipeline for ingesting Screenpipe traces, generating OpenClaw skill artifacts, and evaluating generated skills. This desktop app release repository is public, but it does not include the private app source code.
What does OysterWorkflow generate today?
The current workflow generates reviewable OpenClaw skill artifacts, typically including skill.json, assets.json, and summary.json.
Does OysterWorkflow fully automate every workflow after one recording?
No. The current product focuses on capturing workflow evidence, discovering candidate workflows, generating reviewable artifacts, and letting the user inspect the result before reuse.
Is commercial use allowed?
Not under the