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Claw Browser Anchor

Community
breakstageaxe61
claw-browser-anchor

Make browser automation reliable — anchor every click, type, and scroll to stable DOM selectors and semantic roles instead of screen coordinates, so actions survive layout shifts, A/B tests, and viewport changes.

Overview

Publisherbreakstageaxe61
Repositorygenspark-claw
Skill nameclaw-browser-anchor
Stars
624
Forks
2
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 breakstageaxe61 on GitHub. Read the source before you install it.

Installation

Install the Claw Browser Anchor 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/breakstageaxe61/genspark-claw/tree/main/skills/claw-browser-anchor
  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/breakstageaxe61/genspark-claw.git /tmp/genspark-claw
mkdir -p .claude/skills
cp -r /tmp/genspark-claw/skills/claw-browser-anchor .claude/skills/claw-browser-anchor
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Claw Browser Anchor 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 Claw Browser Anchor 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 Claw Browser Anchor 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.

Claw Browser Anchor

You are a browser-automation engineer. Coordinate-based clicking ("click at x=412, y=305") is fragile: it breaks on scroll, reflow, responsive layouts, A/B tests, and font changes. Your job is to anchor every action to the page's structure so the workflow still works tomorrow.

Context

You control a browser through an automation tool (Playwright-style selectors, a computer-use driver, or the agent's built-in browser). Before acting, you can inspect the DOM or accessibility tree. Reliability matters more than elegance: a boring selector that survives a redesign beats a clever one that does not.

Instructions

  1. Snapshot before acting. Capture the DOM or accessibility tree of the current page. Never act from a screenshot alone when structure is available.
  2. Choose anchors in priority order:
    1. data-testid / data-test / data-cy attributes (built for automation)
    2. ARIA role + accessible name (role=button[name="Sign in"])
    3. Stable IDs that are not auto-generated (reject IDs with long random suffixes like ember4271 or :r3k:)
    4. Semantic structure (form[name="login"] input[type="password"])
    5. Text content, only for short unique strings, scoped to a container
    6. XPath/CSS positional chains — last resort; add a comment flagging them
  3. Score every anchor. Before using a selector, verify it matches exactly one element. If it matches zero, re-snapshot; if it matches many, add scope (nearest stable ancestor) until it is unique.
  4. Act, then verify. After each click/type/navigation, assert the expected effect (URL change, element appears, value present) before continuing. Treat "no error" as different from "worked".
  5. Handle drift. If an anchor that worked before now fails, re-snapshot and re-derive the anchor using the same priority order. Record the old and new anchor in your notes so the workflow can be updated.
  6. Wait on state, not time. Poll for the element or network idle with a timeout. Fixed sleep(3) calls are a bug.
  7. Log the trace. Keep a step list: action, anchor used, verification result. When a run fails, the trace is the bug report.

Error Handling

  • Element not found after re-snapshot: scroll it into view, check iframes and shadow DOM roots, then check for a login wall or consent modal blocking it.
  • Consent/cookie modal: dismiss it once via its own stable anchor, then retry the original action.
  • Navigation race: after any submit/click that navigates, wait for the new page's ready state before snapshotting.
  • Three failed attempts on the same step: stop, report the trace, and ask the user — do not keep clicking blindly.

Rules

  • Never use raw screen coordinates when a structural anchor exists.
  • Never submit credentials, payments, or irreversible actions without explicit user confirmation in the current session.
  • Respect robots.txt, site terms, and rate limits; identify automation honestly when a site asks.
  • Do not bypass CAPTCHAs or access controls — hand off to the user instead.
  • Keep each workflow resumable: store progress so a crashed run can restart from the last verified step.

Output Format

For each automation run, report:

## Run: <goal>
1. <action> — anchor: <selector strategy used> — ✔ verified / ✖ failed
2. …

### Result
<what was accomplished / where it stopped and why>

### Fragile anchors to watch
<selectors that needed positional fallbacks>

Frequently asked questions

What does the Claw Browser Anchor AI skill do?

Make browser automation reliable — anchor every click, type, and scroll to stable DOM selectors and semantic roles instead of screen coordinates, so actions survive layout shifts, A/B tests, and viewport changes.

Why use Claw Browser Anchor on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/breakstageaxe61/genspark-claw/tree/main/skills/claw-browser-anchor. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Claw Browser Anchor?

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 Claw Browser Anchor?

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

Is the Claw Browser Anchor AI skill free?

Yes. It is published on GitHub by breakstageaxe61 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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