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Screenpipe Bug Report

OrganizationPopular
screenpipe
screenpipe-bug-report

Turn a recorded software failure into a reproducible bug report with timestamps and observed behavior.

Overview

Publisherscreenpipe
Repositoryscreenpipe
Skill namescreenpipe-bug-report
Stars
21.9K
Forks
2.2K
Bundled files
Instructions only
Links
Skill sourceRepositoryHomepage
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by screenpipe on GitHub. Read the source before you install it.

Installation

Install the Screenpipe Bug Report AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/screenpipe/screenpipe/tree/main/crates/screenpipe-core/assets/skills/screenpipe-bug-report
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/screenpipe/screenpipe.git /tmp/screenpipe
mkdir -p .claude/skills
cp -r /tmp/screenpipe/crates/screenpipe-core/assets/skills/screenpipe-bug-report .claude/skills/screenpipe-bug-report
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Screenpipe Bug Report in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Screenpipe Bug Report on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Screenpipe Bug Report is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

bug report

Resolve the affected app, failure, and approximate time. Use screenpipe-api to inspect the relevant activity and frames; use transcripts only for additional context. Recover the actual sequence before, during, and after the failure.

Write reproduction steps, expected behavior from the user's intent or documented contract, actual behavior, environment/version when verified, and the smallest useful evidence links. Separate visible symptoms from hypotheses about the cause. Mark steps that could not be reproduced.

Remove credentials, unrelated screen content, personal identifiers, and private business metrics from shareable evidence. Do not repeat destructive actions to reproduce the bug. Return a draft report unless issue creation is explicitly authorized.

Frequently asked questions

What does the Screenpipe Bug Report AI skill do?

Turn a recorded software failure into a reproducible bug report with timestamps and observed behavior.

Why use Screenpipe Bug Report on TypingMind?

Because you install it once and use it with any model. Screenpipe Bug Report is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Screenpipe Bug Report in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/screenpipe/screenpipe/tree/main/crates/screenpipe-core/assets/skills/screenpipe-bug-report. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Screenpipe Bug Report?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Screenpipe Bug Report?

As many as you like. As long as a model supports skills, you can use Screenpipe Bug Report with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Screenpipe Bug Report AI skill free?

It is published on GitHub by screenpipe. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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