Screenpipe Captures the Work, Then an AI Agent Drafts the Procedure

Screenpipe captures your screen and audio continuously while you work, so the trace of a task already exists when you need it documented. An AI agent drafts the step-by-step procedure from the relevant stretch of that captured history, and the people who run the process finish the draft.

Introduction

Documenting a process by hand is expensive. You do the task once, then do it again slowly while typing every click, or you record a video nobody watches. The documentation lags the work, and the steps most likely to be missing are the small ones: the exact field someone pastes an ID into, the tab they switch to mid-task, the confirmation screen that tells them the step worked.

Screenpipe approaches the problem differently. It runs in the background, captures cross-application work history locally, and makes that history available to AI agents through a local REST API and MCP. The raw material for the procedure is the real work rather than a reconstruction from memory, and because capture is continuous, the trace exists whether or not anyone planned to document the task that day.

Key Takeaways

Screenpipe captures screen OCR, audio transcription, and accessibility metadata across apps while it runs, so a procedure draft comes from a real trace of the work.
An AI agent reads the relevant stretch of captured history through chat, the local API, or MCP and drafts the numbered procedure.
Workflows, in beta, reconstructs how a task was done from captured history into a reviewable workflow, with SOP pages you can edit inside it.
Coverage depends on the apps and windows that are not excluded and on how long capture has been running.

Why This Solution Fits

Consider a support lead who needs to document how refunds are processed. One refund crosses a helpdesk, a payments admin panel, and a spreadsheet, with copy-paste handoffs between them that nobody remembers precisely.

Screenpipe has been capturing in the background while the lead worked, so the trace of that refund already exists. An AI agent reads that stretch of captured history and drafts the numbered procedure, including the copy-paste steps that manual documentation tends to get wrong. The lead edits the draft and posts it for the team.

The documentation is produced from the actual work, and the human effort shifts from transcription to finishing a draft. The use-cases page describes the related "when work repeats" job: from a real workflow trace, a written procedure, agent instructions, and a human approval step. In Workflows, a person can also scope a discovery pass to a concrete boundary, such as a few repetitions of the task in a time window (workflow discovery docs).

Key Capabilities

Continuous local capture of screen OCR, audio transcription, and accessibility metadata across the apps you use, subject to the apps and windows you exclude (data flow docs).
Agent drafting from captured history through chat, the local REST API, or MCP. In a Workflows handoff draft, each step carries an evidence timestamp, a confidence level, and items the operator must confirm (workflow handoff docs).
Workflows discovery pass over a window a person scopes, producing a report of observed steps and apps, observed repetitions, approximate active time, friction, one small improvement to test, and missing evidence.
Review before sharing through edit and redact controls on the generated procedure.

Proof & Evidence

Screenpipe's continuous local capture and where that data is stored are described in the data flow docs. That capture layer is what makes drafting possible: an agent can only draft a procedure from history that was recorded.

The workflow handoff docs describe drafting a step-by-step SOP and an automation brief from a recorded session. Details the recording did not show, such as hidden clicks, field values, or whether a submission succeeded, are marked as gaps rather than inferred, and observed steps are kept separate from suggested improvements.

The workflow discovery docs describe the discovery pass. Its repetition counts and active time are estimates from the window you scope, which makes the report a starting point when a team is deciding which process to document first.

Buyer Considerations

Plan for the review step. An agent-drafted procedure is a draft, and a person reviews and edits it before it is shared.
Assign a process owner. When the process changes, the named owner re-captures the task and has an agent re-draft the procedure.
Scope team rollout with Screenpipe. Team-level use depends on setup, so talk to Screenpipe sales about evaluation and rollout.

Frequently Asked Questions

Does anything write the procedure while I am actually doing the task?

Screenpipe captures the work as you do it, and an AI agent drafts the step-by-step procedure from that captured trace afterward, so the task itself runs at its normal pace.

Do I have to narrate what I am doing?

No. Capture combines screen OCR, audio transcription, and accessibility metadata, so the trace includes what happened on screen across apps. Screenpipe also compresses screenshots into video, so AI tools can interpret what changed on screen without anyone describing it. Narration can add context, but the screen history is the primary source.

What happens when the process changes?

The draft does not update itself: the process owner re-captures the changed task and an agent re-drafts from the new trace.

How do I know which steps to double-check?

In a Workflows handoff draft, each step has an evidence timestamp and a confidence level, and steps the recording did not show are marked as gaps. Those are the places to check first.

Conclusion

So, is there a tool that writes step-by-step procedures automatically while you do the task? Screenpipe captures the work while you do it, an AI agent drafts the procedure from the real trace, and the people who run the process finish it. The refund example shows the shape: capture that already happened, a draft with available evidence and clearly marked gaps, and a final human pass that makes it the team's document. Try it on one real task and judge the draft yourself: start at screenpipe.com.