Awesome Webpage Research

OrganizationPopular

TokenRhythm

awesome-webpage-research

Single-pass mini research for AwesomeWebpageMetaSkill: produce a short cited topic brief from one bounded web-search round. Not a general deep-research replacement.

Overview

Publisher	TokenRhythm
Repository	`opensquilla`
Skill name	`awesome-webpage-research`
Stars	7K
Forks	566
Bundled files	Instructions only
License	Apache-2.0
Links	Skill source Repository Homepage

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 TokenRhythm on GitHub. Read the source before you install it.

Installation

Install the Awesome Webpage Research AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/TokenRhythm/opensquilla/tree/main/src/opensquilla/skills/bundled/awesome-webpage-research

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

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/TokenRhythm/opensquilla.git /tmp/opensquilla
mkdir -p .claude/skills
cp -r /tmp/opensquilla/src/opensquilla/skills/bundled/awesome-webpage-research .claude/skills/awesome-webpage-research

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Awesome Webpage Research 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 Awesome Webpage Research 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 Awesome Webpage Research 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.

Awesome Webpage Research (mini)

Lightweight, single-pass topic research used only by AwesomeWebpageMetaSkill. Produce a concise topic brief with a short citation list so the page planner has factual anchors. This is not a replacement for the bundled deep-research skill; do not invoke it for general literature reviews or multi-round investigations.

Inputs

The caller supplies:

question: the topic, audience, language, style, and webpage context to research.

Protocol

Single round. Three steps. No iteration, no plan.json, no state file.

Identify 3-5 focused sub-questions that the page planner needs answered to ground page sections. Cover what the topic is, why it matters, key facts, common misconceptions, and at most one stat or date anchor. Do not exceed 5 sub-questions.
Run one bounded web-search round: at most one search query per sub-question. Use web-search for every language. Prefer recent, reputable sources. Stop at one usable source per sub-question; do not chase broader coverage and do not run a second round.
Compile a single brief (target ~300-500 words) containing:
- one paragraph topic summary
- one paragraph "key facts" with inline [1]-style citation tags
- a Sources list of 3-5 entries formatted as [n] Title — URL
- a final Page anchors: line listing 3-5 short phrases that can become section headings or callouts on the webpage

Rules

Do not iterate. One search round, one synthesis pass. Return as soon as the brief is written.
Do not fetch full articles. Use search snippets; perform at most one quick fetch per sub-question if a snippet is unusable.
Do not invent citations. Every [n] must map to a source in the Sources list. If a source cannot be cited, drop the claim instead of fabricating one.
Do not produce a multi-page literature review. Cap the brief at ~500 words.
Do not search for images, audio, or video media here; media acquisition is handled by other meta-skill steps.
Do not call deep-research, summarize, or any meta-skill from this step.
If the search round returns nothing usable, prepend a single line RESEARCH_THIN to the brief and continue with a question-only summary without inventing citations or sources.

Output

Return only the brief text. No methodology notes, no per-source commentary, no JSON wrapper. The caller will truncate this output before feeding it to the page planner.

Frequently asked questions

What does the Awesome Webpage Research AI skill do?

Single-pass mini research for AwesomeWebpageMetaSkill: produce a short cited topic brief from one bounded web-search round. Not a general deep-research replacement.

Why use Awesome Webpage Research on TypingMind?

Because you install it once and use it with any model. Awesome Webpage Research 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 Awesome Webpage Research in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/TokenRhythm/opensquilla/tree/main/src/opensquilla/skills/bundled/awesome-webpage-research. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Awesome Webpage Research?

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 Awesome Webpage Research?

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

Is the Awesome Webpage Research AI skill free?

Yes. It is published on GitHub by TokenRhythm under the Apache-2.0 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Awesome Webpage Research (mini)

Inputs

Protocol

Rules

Output

Frequently asked questions

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