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Benchmark Browsing Skills

Organization
browsing-skills
benchmark-browsing-skills

Use when benchmarking browsing-skills actions, comparing a maintained site skill against a no-skill browser agent, measuring OpenAI API token usage, wall time, API calls, browser/tool calls, and result quality. Trigger whenever the user asks to benchmark a browsing skill, compare with/without skill, measure token or time savings, or update benchmark tables in this repo.

Overview

Publisherbrowsing-skills
Repositorybrowsing-skills
Skill namebenchmark-browsing-skills
Stars
120
Forks
19
Bundled files
1
LicenseMIT
Links
Skill sourceRepository
  • 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.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by browsing-skills on GitHub. Read the source before you install it.

Installation

Install the Benchmark Browsing Skills 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/browsing-skills/browsing-skills/tree/main/.agents/skills/benchmark-browsing-skills
  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/browsing-skills/browsing-skills.git /tmp/browsing-skills
mkdir -p .claude/skills
cp -r /tmp/browsing-skills/.agents/skills/benchmark-browsing-skills .claude/skills/benchmark-browsing-skills
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Benchmark Browsing Skills 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 Benchmark Browsing Skills 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 Benchmark Browsing Skills 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.

Benchmark Browsing Skills

Use this skill to run and document fair benchmarks for actions in this repo.

The benchmark compares two agents on the same live browser task:

  • With skill: loads the site action index plus only the action-facing parts of one action reference, then runs the maintained action code.
  • Without skill: receives browser access but no skill/reference, inspects the live page, derives extraction logic, and iterates until success or timeout.

For official numbers, prefer OpenAI API-separated runs over Codex subagents. Subagents are useful for quick qualitative comparisons, but API runs give explicit token accounting and cleaner cost comparison.

Use the same browser layer and session state for both branches. For actions that depend on login, personalization, region, cart state, or existing cookies, prefer Chrome Bridge /run-action against the user's loaded Chrome session. Use Playwright only for public, unauthenticated actions or when you intentionally create an equivalent browser profile for both branches.

Workflow

  1. Identify the website, action, target URL/query, browser layer, expected output fields, session requirements, and success criteria.
  2. Read only the matching site SKILL.md and action reference from skills/<domain>/references/<action>.md; exclude benchmark history and other non-action prose from the measured with-skill prompt.
  3. Run the with-skill API pass with the skill index/reference available.
  4. Run the without-skill API pass without skill files; provide only browser tools and live page observations.
  5. Capture tokens, API calls, wall time, browser calls, and result quality for both passes.
  6. Record results in:
    • BENCHMARKS.md
    • the site skills/<domain>/SKILL.md benchmark table
    • the action reference ## Benchmark section

Read references/api-benchmark-protocol.md before designing or running a benchmark.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Benchmark Browsing Skills AI skill do?

Use when benchmarking browsing-skills actions, comparing a maintained site skill against a no-skill browser agent, measuring OpenAI API token usage, wall time, API calls, browser/tool calls, and result quality. Trigger whenever the user asks to benchmark a browsing skill, compare with/without skill, measure token or time savings, or update benchmark tables in this repo.

Why use Benchmark Browsing Skills on TypingMind?

Because you install it once and use it with any model. Benchmark Browsing Skills 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 Benchmark Browsing Skills in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/browsing-skills/browsing-skills/tree/main/.agents/skills/benchmark-browsing-skills. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Benchmark Browsing Skills?

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 Benchmark Browsing Skills?

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

Is the Benchmark Browsing Skills AI skill free?

Yes. It is published on GitHub by browsing-skills 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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