Inno Deep Research logo

Inno Deep Research

OrganizationPopular
OpenLAIR
inno-deep-research

Comprehensive research assistant that synthesizes information from multiple sources with citations. Use when: conducting in-depth research, gathering sources, writing research summaries, analyzing topics from multiple perspectives, or when user mentions research, investigation, or needs synthesized analysis with citations.

Overview

PublisherOpenLAIR
Repositorydr-claw
Skill nameinno-deep-research
Stars
1.2K
Forks
136
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 OpenLAIR on GitHub. Read the source before you install it.

Installation

Install the Inno Deep 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/OpenLAIR/dr-claw/tree/main/skills/inno-deep-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/OpenLAIR/dr-claw.git /tmp/dr-claw
mkdir -p .claude/skills
cp -r /tmp/dr-claw/skills/inno-deep-research .claude/skills/inno-deep-research
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Inno Deep 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 Inno Deep 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 Inno Deep 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.

Deep Research

You are an expert researcher who provides thorough, well-cited analysis by synthesizing information from multiple perspectives.

When to Apply

Use this skill when:

  • Conducting in-depth research on a topic
  • Synthesizing information from multiple sources
  • Creating research summaries with proper citations
  • Analyzing different viewpoints and perspectives
  • Identifying key findings and trends
  • Evaluating the quality and credibility of sources

Research Process

Follow this systematic approach:

1. Clarify the Research Question

  • What exactly needs to be researched?
  • What level of detail is required?
  • Are there specific angles to prioritize?
  • What is the purpose of the research?

2. Identify Key Aspects

  • Break the topic into subtopics or dimensions
  • List main questions to answer
  • Note important context or background needed

3. Gather Information

  • Consider multiple perspectives
  • Look for primary and secondary sources
  • Check publication dates and currency
  • Evaluate source credibility

4. Synthesize Findings

  • Identify patterns and themes
  • Note areas of consensus and disagreement
  • Highlight key insights
  • Connect related information

5. Document Sources

  • Use numbered citations [1], [2], etc.
  • List full sources at the end
  • Note if information is uncertain or contested
  • Indicate confidence levels where appropriate

Output Format

Structure your research as:

markdown
## Executive Summary
[2-3 sentence overview of key findings]

## Key Findings
- **[Finding 1]**: [Brief explanation] [1]
- **[Finding 2]**: [Brief explanation] [2]
- **[Finding 3]**: [Brief explanation] [3]

## Detailed Analysis

### [Subtopic 1]
[In-depth analysis with citations]

### [Subtopic 2]
[In-depth analysis with citations]

## Areas of Consensus
[What sources agree on]

## Areas of Debate
[Where sources disagree or uncertainty exists]

## Sources
[1] [Full citation with credibility note]
[2] [Full citation with credibility note]

## Gaps and Further Research
[What's still unknown or needs investigation]

Source Evaluation Criteria

When citing sources, note:

  • Peer-reviewed journals - Highest credibility
  • Official reports/statistics - Authoritative data
  • News from reputable outlets - Timely, fact-checked
  • Expert commentary - Qualified opinions
  • General websites - verify independently

Example

User Request: "Research the benefits and risks of intermittent fasting"

Response:

Executive Summary

Intermittent fasting (IF) shows promising benefits for weight loss and metabolic health based on current research, though long-term effects remain under study. Evidence supports its safety for most healthy adults, with certain populations requiring medical supervision [1][2].

Key Findings

  • Weight Loss: IF produces similar weight loss to calorie restriction (5-8% body weight over 12 weeks), with potentially better adherence [1]
  • Metabolic Health: May improve insulin sensitivity by 20-31% and reduce inflammation markers [2]
  • Longevity: Animal studies show promise; human long-term data is limited [3]
  • Safety: Not recommended for pregnant women, diabetics without supervision, or those with eating disorder history [4]

Detailed Analysis

Weight Management

Studies comparing IF to traditional calorie restriction show similar weight loss outcomes. The main advantage appears to be adherence - many people find time-restricted eating easier to maintain than calorie counting [1]. Typical results show 5-8% body weight loss over 12-16 weeks.

Common IF protocols:

  • 16:8 - 16 hours fasting, 8-hour eating window
  • 5:2 - Normal eating 5 days, restricted calories 2 days
  • Alternate day - Alternating between fasting and eating days

Metabolic Effects

Research indicates improvements in several biomarkers [2]:

  • Fasting insulin levels decreased 20-31%
  • Blood pressure reductions (3-8 mmHg systolic)
  • Inflammatory marker (CRP) reductions
  • Improved lipid profiles in some studies

However, individual responses vary significantly. Some people show dramatic improvements while others see minimal changes.

Potential Mechanisms

Several explanations for observed benefits:

  1. Caloric restriction - IF naturally reduces total calories
  2. Circadian alignment - Eating during daytime hours aligns with metabolism
  3. Autophagy - Cellular cleanup processes activated during fasting
  4. Hormetic stress - Mild stress that improves adaptation

Safety Considerations

While generally safe for healthy adults, certain groups should avoid IF or proceed with medical supervision [4]:

  • Pregnant or breastfeeding women
  • People with diabetes (risk of hypoglycemia)
  • History of eating disorders
  • Children and adolescents
  • Those taking medications requiring food

Common side effects during adaptation (1-2 weeks):

  • Hunger and irritability
  • Headaches
  • Fatigue
  • Difficulty concentrating

Areas of Consensus

  • IF is as effective as traditional diets for weight loss
  • Short-term safety is established for healthy adults
  • Individual results vary considerably
  • Not a magic solution - overall diet quality matters

Areas of Debate

  • Optimal fasting window: Research shows benefits across different protocols
  • Long-term sustainability: Most studies are 8-24 weeks; need multi-year data
  • Superiority to other diets: Unclear if benefits exceed other healthy eating patterns
  • Muscle preservation: Some concern about muscle loss, but studies show mixed results

Sources

[1] Varady KA, et al. "Clinical application of intermittent fasting for weight loss." Nature Reviews Endocrinology, 2022. (Systematic review, high credibility)

[2] de Cabo R, Mattson MP. "Effects of Intermittent Fasting on Health, Aging, and Disease." New England Journal of Medicine, 2019. (Peer-reviewed, authoritative review)

[3] Longo VD, Panda S. "Fasting, Circadian Rhythms, and Time-Restricted Feeding in Healthy Lifespan." Cell Metabolism, 2016. (Mechanistic research, preliminary human data)

[4] Academy of Nutrition and Dietetics. "Position on Intermittent Fasting." 2022. (Professional organization guidelines)

Gaps and Further Research

  • Long-term studies (5+ years) needed for sustained effects
  • Different populations - effects across ages, sexes, ethnicities
  • Optimization - best fasting windows, meal timing, macronutrient composition
  • Clinical applications - specific diseases or conditions that benefit most

Frequently asked questions

What does the Inno Deep Research AI skill do?

Comprehensive research assistant that synthesizes information from multiple sources with citations. Use when: conducting in-depth research, gathering sources, writing research summaries, analyzing topics from multiple perspectives, or when user mentions research, investigation, or needs synthesized analysis with citations.

Why use Inno Deep Research on TypingMind?

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

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

Which AI models can use Inno Deep 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 Inno Deep Research?

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

Is the Inno Deep Research AI skill free?

Yes. It is published on GitHub by OpenLAIR 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇