automate-this

Overview of automate-this skill

What automate-this does

The automate-this skill turns a screen recording of a repetitive task into an automation plan and draft scripts. Instead of asking you to describe every click manually, it extracts frames from the video, transcribes narration when available, reconstructs the workflow, and suggests ways to automate it using tools already on your machine.

Who should use automate-this

automate-this is best for people who already have a real manual workflow but have not documented it cleanly. Good fits include ops work, QA routines, file handling, web admin chores, repetitive terminal tasks, and cross-app desktop processes where a plain text prompt would miss important details.

The real job-to-be-done

Most users do not need a generic “automation idea.” They need help converting a messy, observed process into something scriptable. The core value of automate-this for Workflow Automation is that it starts from evidence in the recording, not from memory, which reduces skipped steps and hidden assumptions.

What makes automate-this different from a normal prompt

A normal prompt depends on the user describing the process accurately. The automate-this skill instead works from:

• extracted frames for step sequence
• audio narration when present
• reconstruction of intent and decision points
• automation options at different complexity levels

That makes it more useful when the workflow spans UI actions, terminal commands, and judgment calls that are easy to forget in a written summary.

What matters before you install or invoke it

Adoption mainly depends on three things:

• you can provide a usable screen recording
• ffmpeg is available locally
• if narration matters, a Whisper tool is available or you are willing to proceed without transcription

If those are true, automate-this install and first use are straightforward. If not, results degrade quickly because the skill relies on observable evidence from the recording.

When automate-this is a strong fit

Use automate-this when:

• you repeat the same task often enough that scripting is worth it
• the workflow is easier to show than explain
• you want multiple automation paths, from simple scripts to more robust approaches
• you want the assistant to infer structure from a recording instead of starting from a blank prompt

When automate-this is not the right tool

Skip it if:

• the task is already well specified in text
• there is no recording and no reliable step description
• the process depends on hidden business rules not visible in the video
• the task needs deep app-specific API knowledge that is not observable from the recording alone

How to Use automate-this skill

Install context for automate-this skill

The repository evidence points to a skill definition in skills/automate-this/SKILL.md. In a GitHub Copilot skills setup, users typically add and invoke the skill through their skills workflow rather than as a standalone package. If you use a skills manager, the common pattern is:

npx skills add github/awesome-copilot --skill automate-this

Then invoke automate-this from your agent environment with a prompt that includes the video path and your goal.

Prerequisites that block first-run success

The most important setup check in the upstream skill is local tooling:

• ffmpeg is required
• whisper or whisper-cpp is optional, but useful for narrated recordings

If ffmpeg is missing, install it first:

• macOS: brew install ffmpeg

If the recording includes narration and you want transcription:

• pip install openai-whisper
• or brew install whisper-cpp

Without ffmpeg, the automate-this skill cannot do its extraction workflow. Without Whisper, it can still analyze visuals only.

What input automate-this needs

The minimum useful input is:

• a path to a screen recording file
• a short statement of what outcome you want
• any constraints on allowed tools or runtime environment

A strong input also adds:

• what machine or OS the process runs on
• whether browser automation is acceptable
• whether you prefer shell, Python, AppleScript, PowerShell, or another automation style
• whether the task should be quick-and-dirty or production-safe

How automate-this actually works in practice

The skill’s documented workflow is roughly:

1. check ffmpeg and optionally Whisper availability
2. extract frames from the video at a coarse interval
3. extract audio and transcribe it if useful
4. reconstruct the step-by-step workflow
5. identify repetitive actions, branches, and likely intent
6. propose automation approaches at different complexity levels
7. draft working automation using tools already installed if possible

That means better recordings lead directly to better scripts.

How to write a prompt that invokes automate-this well

A weak prompt:

• “Automate this video.”

A stronger automate-this usage prompt:

• “Use automate-this on ~/Desktop/invoice-upload.mp4. I’m on macOS. Please analyze the recording, reconstruct the exact workflow, identify repeated steps, and propose three automation options: a quick shell-based helper, a browser automation approach, and the most reliable long-term approach. Prefer tools already installed. If narration is missing or unclear, infer steps from frames and call out uncertainty.”

Why this works:

• it names the file
• it sets OS context
• it asks for workflow reconstruction before code
• it requests tradeoff-based output, not just one script
• it tells the skill how to handle ambiguity

Turn a rough goal into a complete automate-this request

Use this template:

• video path
• operating system
• target apps/sites involved
• preferred automation stack
• reliability vs speed preference
• permissions or security limits
• expected final outcome

Example:

• “Run automate-this on ~/Desktop/reporting-routine.mov. Windows 11, Chrome, Excel, internal web app. I can use Python and PowerShell but not paid SaaS tools. Goal: open the report page, export CSV, rename it by date, move it to a shared folder, and notify me if export fails. Give me an MVP script and a safer version with validation.”

Best workflow for first use

For a first pass, ask for output in this order:

1. observed workflow summary
2. unclear or risky steps
3. candidate automation approaches
4. recommended approach with reasoning
5. implementation draft
6. setup and run instructions
7. validation checklist

This structure prevents the common mistake of generating code before the task is actually understood.

What to read first in the repository

For this skill, SKILL.md is the primary source and the only meaningful file surfaced in the tree. Read it in this order:

1. prerequisites check
2. extraction phase
3. frame extraction details
4. audio extraction and transcription guidance
5. later sections on workflow reconstruction and automation generation

Because there are no visible helper scripts or reference folders, the value lives in the procedure described in SKILL.md, not in packaged tooling.

Practical tips that improve automate-this output quality

To get better automate-this usage results:

• record the whole process from start to finish without skipping steps
• narrate why you are doing each action, not just what you click
• keep zoom and window switching manageable
• avoid ultra-fast cursor movement
• show filenames, URLs, and field names clearly
• include one full successful run, not a partial example

These details help the skill infer intent and produce automation that survives outside the demo.

Constraints and tradeoffs to know upfront

automate-this is good at visible workflows, but its limits matter:

• frame sampling can miss very fast transient actions
• silent recordings lose intent that narration could provide
• hidden credentials, two-factor steps, and internal policy rules will not be inferred safely
• UI-driven automations may be more brittle than API-based alternatives

Use it to discover and draft automation, then harden the result with explicit constraints and validation.

automate-this skill FAQ

Is automate-this better than just describing my workflow in text?

Usually yes when the workflow is hard to describe completely. automate-this can recover missed steps from the recording and cross-check narration against on-screen actions. If your process is already clearly documented in text, a normal prompt may be faster.

Is automate-this beginner-friendly?

Yes, especially for users who know the task but do not know how to specify it cleanly. The main beginner hurdle is environment setup: ffmpeg is mandatory, and transcription support may need an extra install.

Do I need narration in the recording?

No, but it helps a lot. The skill can proceed with visual analysis only. Narration improves explanation of intent, branch decisions, and edge cases that are not obvious from clicks alone.

What kinds of automation can automate-this suggest?

The automate-this skill is designed to propose multiple complexity levels. In practice, that can mean a simple helper script, a more structured local automation, or a more reliable long-term implementation depending on the workflow and tools available.

Does automate-this require special repository files?

No extra support files are visible here beyond SKILL.md. That makes the skill easy to inspect, but it also means you should expect process guidance rather than a bundled toolchain.

When should I not use automate-this for Workflow Automation?

Do not use automate-this for Workflow Automation when the process depends mostly on hidden business rules, private APIs, approval logic, or inaccessible system state. In those cases, a recording alone is not enough to generate dependable automation.

Can automate-this produce production-ready scripts immediately?

Sometimes for simple workflows, but usually the first output should be treated as a strong draft. The safer pattern is to review the reconstructed workflow, test on a sample case, and then tighten error handling and validation.

How to Improve automate-this skill

Give automate-this stronger evidence, not just a longer prompt

The fastest way to improve automate-this results is to improve the recording:

• include the full path from trigger to completion
• speak decision criteria out loud
• show expected outputs
• repeat the task once if the first run contains mistakes

Better source evidence beats extra prompt wording.

Ask for uncertainty reporting

A common failure mode is false confidence about ambiguous UI steps. Tell automate-this to mark:

• guessed actions
• unreadable UI text
• possible branch points
• steps that may need confirmation from you

This changes the output from “plausible script” to “testable automation plan.”

Constrain the automation stack early

If you do not specify tool preferences, the skill may suggest an approach you cannot run or maintain. State things like:

• “Prefer Bash and existing CLI tools”
• “Use Python, not browser RPA”
• “Avoid cloud services”
• “macOS only”
• “Must be runnable by non-admin users”

This is one of the highest-leverage ways to improve the automate-this guide experience.

Request multiple solution levels

A strong prompt asks for:

• quickest workable automation
• most maintainable automation
• most reliable automation

That forces the skill to surface tradeoffs instead of locking onto one implementation path too early.

Provide success criteria for the generated automation

Say what counts as done:

• expected files created
• target system updated
• naming conventions
• notification behavior
• failure handling requirements

Without explicit success criteria, automate-this install may be easy but first-run validation will be vague.

Iterate after the first draft

After the initial result, refine with:

• corrected step order
• missing edge cases
• environment restrictions
• actual errors from test runs
• preference changes after seeing the first proposal

The best use of automate-this is usually two-pass: first reconstruct, then harden.

Common failure modes to watch for

Watch for these issues when reviewing output:

• skipped login or context-setting steps
• fragile selectors or UI assumptions
• no handling for timing, retries, or missing files
• over-automation of a process that should use an API instead
• code that does not match your installed tools

Catching these early improves trust and avoids brittle automation.

How to make the final output more usable

Ask the skill to include:

• prerequisites
• exact run command
• editable variables at the top of the script
• logging or status output
• a small test plan
• rollback or cleanup notes if relevant

This turns a raw draft into something another teammate can actually run.

How to improve automate-this skill in your own workflow

Use automate-this as a front-end discovery tool, then pair it with your normal engineering review. The skill is strongest at observing and structuring a workflow from video evidence; your job is to supply the last-mile constraints, maintenance standards, and environment-specific checks that turn a draft into dependable automation.