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Skill Recorder

Skill Recorder is a Microsoft desktop app for showing an AI agent how you complete a computer task instead of describing the whole workflow from memory.

It records one on-screen work session, uses GitHub Copilot to reconstruct the intent and ordered steps, then can turn the reviewed result into a reusable Skill or scheduled Automation. Use this as a first read, not a recommendation. Open the original project before trusting details like terms, limits, privacy, cost, setup, or safety.

What it is

A recorder for teach-by-example workflows

The desktop app captures clicks, window and app changes, visited pages, and optional spoken narration. After recording, Copilot turns that evidence into an intent and a sequence you can inspect and edit.

Why it stands out

The recording becomes editable instructions

The result is not a blind replay of mouse movements. Skill Recorder aims to generalize one example into a SKILL.md procedure or Automation that prefers an agent's own tools when available.

Availability

Source-built app with a Copilot requirement

The project publishes source-only releases for macOS, Windows 11, and Ubuntu. Installation builds a pinned release on your machine, and analysis requires a GitHub account with Copilot access.

Why it matters

What makes it useful

A familiar task can contain small choices that are hard to remember while writing instructions. Recording the real run gives you a starting sequence to correct, trim, and reuse instead of drafting every step from a blank page.

Notable points

What stands out

Recording, frame extraction, storage, and optional narration transcription happen locally. When you choose Analyze, the project says it sends the event timeline—including window or document titles, clipboard previews, and, on macOS, browser URLs—plus extracted screen images and narration text to GitHub's cloud for Copilot processing.

Before using

What to review

Keep passwords, tokens, confidential documents, private messages, and other sensitive material out of the recording. The project warns that captured material is sent to GitHub when Analyze is used.

Choose a task with clear boundaries. One recording can miss alternate paths, error cases, permissions, and approval points that a reusable skill still needs.

Read and edit the reconstructed intent and steps before generating anything. A recording shows what happened once; it does not prove that every inferred instruction is correct.

Expect a source-build installation rather than a normal prebuilt installer. The documented path downloads a pinned Node.js runtime and builds the selected release locally.

Check the current repository terms and the GitHub Copilot requirements for your intended setup.

Reader fit

Who may find it relevant

People who can demonstrate a routine more easily than they can write a complete agent procedure.

Builders who want an editable SKILL.md starting point from a real workflow.

Teams willing to review captures carefully before sending them for cloud analysis.

Less relevant if the task contains secrets, cannot be safely recorded, needs a prebuilt one-click app, or must avoid GitHub Copilot.

Editorial note

Why LifeHubber lists it

Skill Recorder gives you a teach-by-example starting point: demonstrate the task, inspect what Copilot inferred, then edit the result before it becomes a Skill or Automation. It suits people who are comfortable building the app from source and sending the captured material to Copilot for analysis.

Source links

Source materials

Reader note

Before relying on this entry

LifeHubber lists entries to help readers inspect AI projects, not to endorse them or prove they are safe, suitable, accurate, maintained, or right for a specific use. We do not verify every entry in depth. Before relying on anything listed, review the original materials, terms, privacy practices, limits, and risks that matter for your situation.

What to explore next

Improve the skill after the first recording.

Skill Recorder turns one demonstrated workflow into an editable skill. SkillOpt explores the next problem: using agent trajectories and validation checks to revise an existing skill.

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