Web Research logo

Web Research

Organization
sinaptik-ai
web-research

Use this skill when the user asks to research a topic, find information online, compare options, investigate a question, or compile findings from multiple sources. Trigger for any task that requires searching the web, reading articles, and synthesizing findings into a structured answer.

Overview

Publishersinaptik-ai
Repositorystarpod
Skill nameweb-research
Stars
80
Forks
20
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 sinaptik-ai on GitHub. Read the source before you install it.

Installation

Install the Web Research 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/sinaptik-ai/starpod/tree/main/crates/starpod/skills/web-research
  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/sinaptik-ai/starpod.git /tmp/starpod
mkdir -p .claude/skills
cp -r /tmp/starpod/crates/starpod/skills/web-research .claude/skills/web-research
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Web 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 Web 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 Web 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.

Web Research

Methodology

Follow this structured approach for any research task:

1. Scope the question

Before searching, clarify:

  • What specifically does the user need to know?
  • What format should the answer take? (summary, comparison table, list, report)
  • How deep should the research go? (quick answer vs. comprehensive analysis)

2. Search strategy

  • Start with 2–3 targeted queries using different phrasings
  • Use specific terms, not vague ones: "React server components vs client components performance 2025" beats "React performance"
  • For comparisons, search each option independently before comparing
  • For recent topics, include the year in queries
  • If initial results are thin, broaden terms or try adjacent queries

3. Source evaluation

Prioritize sources in this order:

  1. Official documentation — most reliable for technical topics
  2. Primary sources — research papers, official reports, announcements
  3. Expert analysis — recognized experts, reputable publications
  4. Community consensus — Stack Overflow, GitHub discussions (check vote counts and recency)
  5. News articles — for current events, cross-reference multiple outlets

Red flags: outdated dates, no author attribution, SEO-farm patterns, contradicted by official sources.

4. Synthesize findings

  • Lead with the direct answer, then supporting evidence
  • Note conflicting information across sources and which is more credible
  • Include source URLs for key claims
  • Flag uncertainty: "Based on available data..." or "Sources disagree on..."
  • Distinguish facts from opinions

5. Present results

For quick questions: Direct answer in 2–3 sentences with source link.

For comparisons:

CriteriaOption AOption B
Key metricValueValue
Pros......
Cons......

For deep research: Structure as:

  1. Summary — 2–3 sentence answer
  2. Key findings — bulleted list of important points
  3. Analysis — detailed discussion organized by theme
  4. Sources — numbered list of references used

Common Research Patterns

Product/tool comparison

  1. Search for each product independently
  2. Search for "X vs Y" comparison articles
  3. Check official pricing pages and feature lists
  4. Look for user reviews on neutral platforms
  5. Compile into comparison table

Technical question

  1. Check official documentation first
  2. Search for the specific error message or API
  3. Look at GitHub issues and Stack Overflow
  4. Check release notes if version-specific

Current events / news

  1. Search multiple news sources
  2. Check the date — prefer last 48 hours for breaking news
  3. Look for the primary source (press release, official statement)
  4. Cross-reference facts across 2+ outlets

How-to / tutorial

  1. Find official docs or getting-started guides
  2. Check for community tutorials with recent dates
  3. Verify steps actually work (versions matter)
  4. Prefer tutorials that explain why, not just what

Output Quality Rules

  • Always cite sources — include URLs for every factual claim
  • Always note dates — "As of March 2025, ..." for time-sensitive info
  • Never fabricate — if you can't find it, say so
  • Quantify when possible — "65% of developers prefer X" beats "most developers prefer X"
  • Acknowledge limits — if research was shallow or sources were scarce, say so

Frequently asked questions

What does the Web Research AI skill do?

Use this skill when the user asks to research a topic, find information online, compare options, investigate a question, or compile findings from multiple sources. Trigger for any task that requires searching the web, reading articles, and synthesizing findings into a structured answer.

Why use Web Research on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/sinaptik-ai/starpod/tree/main/crates/starpod/skills/web-research. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Web 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 Web Research?

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

Is the Web Research AI skill free?

Yes. It is published on GitHub by sinaptik-ai 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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