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Browser Walkthrough

Organization
DasDigitaleMomentum
browser-walkthrough

Run Playwright-MCP browser acceptance, agent-observed walkthroughs, or user-attended walkthroughs through the role routing appropriate to each mode, returning a compact evidence-referenced digest.

Overview

PublisherDasDigitaleMomentum
Repositoryopencode-processing-skills
Skill namebrowser-walkthrough
Stars
61
Forks
3
Bundled files
Instructions only
LicenseMIT
Links
  • 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 DasDigitaleMomentum on GitHub. Read the source before you install it.

Installation

Install the Browser Walkthrough 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/DasDigitaleMomentum/opencode-processing-skills/tree/main/skills/browser-walkthrough
  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/DasDigitaleMomentum/opencode-processing-skills.git /tmp/opencode-processing-skills
mkdir -p .claude/skills
cp -r /tmp/opencode-processing-skills/skills/browser-walkthrough .claude/skills/browser-walkthrough
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Browser Walkthrough 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 Browser Walkthrough 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 Browser Walkthrough 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.

Skill: Browser Walkthrough

Use available Playwright MCP/browser tools to exercise and observe a browser journey. This skill does not install, provision, or configure Playwright and does not create a browser-specific persona.

Modes and Role Routing

Select one mode before using browser tools. Existing personas remain defined by the kind of delegation:

  1. Automated browser acceptance — Implementer-owned
    • Use during approved execute-work-package EXECUTE work when browser behavior is part of implementation verification.
    • Keep the approved Blueprint, targeted-then-broad verification sequence, and final verify command authoritative.
    • Exercise the acceptance journey autonomously and return evidence through the execution digest.
  2. Agent-observed walkthrough — Delegate-owned
    • Use when an agent must inspect, explain, or evaluate an existing browser journey without owning implementation.
    • The Delegate owns observations, hypothesis/evidence/decision cycles, and the walkthrough digest; separable evidence retrieval may still go to retriever.
  3. User-attended walkthrough — Maintainer-coordinated, optionally Delegate-executed
    • Use when the user participates in or directs the journey while it is in progress.
    • The Maintainer owns the user conversation and attended decision points. A Delegate may execute each bounded browser segment and return when user input is needed.
    • Resume the same Delegate task_id after user input when it is available; otherwise use a fresh bounded delegation.

Do not route any mode to a browser-runner agent or model alias.

Workflow

  1. State the selected mode, journey objective, starting location, and observable success condition.
  2. Use the available Playwright MCP/browser navigation, accessibility, interaction, console, network, screenshot, and tab tools needed for that journey.
    • A lighter Delegate such as delegate-fast is appropriate for bounded mechanical navigation and observation.
    • Use retriever for separable browser evidence retrieval, not as the owner of an iterative journey or attended interaction.
  3. Prefer compact accessibility queries and targeted evidence. Keep large accessibility snapshots, DOM output, console logs, traces, screenshots, and similar raw evidence out of the owning or primary response:
    • save potentially large tool output to a predictable evidence path when the tool supports it;
    • otherwise use the owning role's existing /tmp/opencode/ spooling, focused filtering, or retriever evidence-routing behavior;
    • retain only paths plus compact decisive observations in the active context.
  4. Treat each completed browser journey, or each bounded browser hypothesis/evidence/decision cycle, as one checkpoint unit. Consult the returned input telemetry before deliberately beginning another context-heavy browser unit; unknown telemetry remains unknown.
  5. Record the observed result, any failure point, evidence paths, and browser cleanup performed or still pending.

Output Contract

Return only a compact digest with these fields:

  • Outcome: succeeded | failed | blocked
  • Mode: automated acceptance | agent-observed | user-attended
  • Steps: concise ordered journey steps
  • Results: decisive observed behavior and acceptance result
  • Failure: concise failure point and message, or none
  • Evidence paths: paths or none; never inline large raw evidence
  • Cleanup: browser cleanup performed or still pending

For automated browser acceptance, incorporate these fields into the Implementer's canonical execution digest rather than emitting a second competing result format.

For a user-attended walkthrough, return this digest at each actual user-interaction point and resume the retained Delegate session after the Maintainer obtains the user's input when that continuation remains useful.

Constraints

  • Use only Playwright MCP/browser capabilities already available in the active harness.
  • Do not provision, install, or configure Playwright.
  • Do not create a new persona or model alias for browser work.
  • Do not replace the owning role's write boundary, approval gate, verification contract, or evidence-routing rules.

Frequently asked questions

What does the Browser Walkthrough AI skill do?

Run Playwright-MCP browser acceptance, agent-observed walkthroughs, or user-attended walkthroughs through the role routing appropriate to each mode, returning a compact evidence-referenced digest.

Why use Browser Walkthrough on TypingMind?

Because you install it once and use it with any model. Browser Walkthrough 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 Browser Walkthrough in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/DasDigitaleMomentum/opencode-processing-skills/tree/main/skills/browser-walkthrough. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Browser Walkthrough?

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 Browser Walkthrough?

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

Is the Browser Walkthrough AI skill free?

Yes. It is published on GitHub by DasDigitaleMomentum under the MIT license. 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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