Agent skill

Inno Deep Research

by LigphiDonk in LigphiDonk/Oh-my--paper

Comprehensive research assistant that synthesizes information from multiple sources with citations.

MITAuto-check passedResearch & Science

Install Inno Deep Research

skills CLI
$ npx skills add LigphiDonk/Oh-my--paper --skill inno-deep-research -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install LigphiDonk/Oh-my--paper inno-deep-research --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/LigphiDonk/Oh-my--paper.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/inno-deep-research .claude/skills/inno-deep-research && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
inno-deep-research
GitHub stars
739
Used in
3 other repos
Token cost
~2.2k tokens
SKILL.md length
886 words
Files
1
Skills in repo
27
Repo updated
First seen
Licence
MIT

At a glance

Comprehensive research assistant that synthesizes information from multiple sources with citations.

  • Works in 5 steps: Clarify the Research Question → Identify Key Aspects → Gather Information → …
  • Tasks that involve Deep research
  • SKILL.md covers Canonical Summary, Trigger Rules, Resource Use Rules and Execution Contract, plus 13 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Inno Deep Research is an agent skill from LigphiDonk/Oh-my--paper. Comprehensive research assistant that synthesizes information from multiple sources with citations.

Its SKILL.md is about 2.2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Research & Science, covering Deep research. The repository describes itself as: A Claude Code plugin that turns your terminal into an autonomous research lab — literature survey, experiment execution, paper writing, all in one pipeline. The licence is MIT.

When your agent uses it

  • Tasks that involve Deep research

Example prompts

  • “/inno-deep-research”

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Clarify the Research Question
  2. Identify Key Aspects
  3. Gather Information
  4. Synthesize Findings
  5. Document Sources

What it can do on your machine

Read from SKILL.md and the folder at commit 6baece9. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Inno Deep Research loads about 2.2k tokens when it runs. Until then it costs about 30 tokens; SKILL.md has 886 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~30
When it runs · the whole SKILL.md, loaded when a task matches
~2.2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from LigphiDonk/Oh-my--paper at commit 6baece9, republished under its MIT licence (© LigphiDonk). 886 words, ~2,208 tokens.

Download SKILL.mdSave it as .claude/skills/inno-deep-research/SKILL.md (or your agent's skills folder).
name
inno-deep-research
description
Comprehensive research assistant that synthesizes information from multiple sources with citations.
id
inno-deep-research
version
1.0.0
stages
survey, ideation, experiment, publication
tools
read_file, search_project, write_file
summary
Comprehensive research assistant that synthesizes information from multiple sources with citations. Use when: conducting in-depth research, gathering sources…
primaryIntent
research
intents
research
capabilities
search-retrieval
domains
general
keywords
inno-deep-research, survey, search-retrieval, inno, deep, research, comprehensive, assistant, that, synthesizes, information, from

inno-deep-research

Canonical Summary

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...

Trigger Rules

Use this skill when the user request matches its research workflow scope. Prefer the bundled resources instead of recreating templates or reference material. Keep outputs traceable to project files, citations, scripts, or upstream evidence.

Resource Use Rules

  • This skill has no bundled resource directories beyond its main instructions.

Execution Contract

  • Resolve every relative path from this skill directory first.
  • Prefer inspection before mutation when invoking bundled scripts.
  • If a required runtime, CLI, credential, or API is unavailable, explain the blocker and continue with the best manual fallback instead of silently skipping the step.
  • Do not write generated artifacts back into the skill directory; save them inside the active project workspace.

Upstream Instructions

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
Show full SKILL.md (337 more words)Show less
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

© LigphiDonk, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/inno-deep-research of LigphiDonk/Oh-my--paper.

Open the folder on GitHubat commit 6baece9

Used in 3 other repositories

We found 4 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 3 other GitHub owners. This page covers the copy in LigphiDonk/Oh-my--paper, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Inno Deep Research next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Inno Deep Research compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Inno Deep Research this skillLigphiDonk/Oh-my--paper7393 repos~2.2kAutomated safety check: PassMIT
GitHub Deep Researchbytedance/deer-flow84k4 repos~1.3kAutomated safety check: PassMIT
Deep Research WorkflowTokenRhythm/opensquilla7.1k—~1.3kAutomated safety check: PassApache-2.0
Deep Researchsanjay3290/ai-skills4329 repos~683Automated safety check: NotesApache-2.0
Horizontal-Vertical Deep ResearchKKKKhazix/khazix-skills21k—~2.1kAutomated safety check: PassMIT
Academic Research PipelineImbad0202/academic-research-skills51k—~15kAutomated safety check: PassCustom licence

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Questions about Inno Deep Research

What does Inno Deep Research do?

Comprehensive research assistant that synthesizes information from multiple sources with citations. Inno Deep Research is an agent skill from LigphiDonk/Oh-my--paper. Comprehensive research assistant that synthesizes information from multiple sources with citations.

When should I use Inno Deep Research?

Inno Deep Research fits situations like: tasks that involve Deep research.

How do I install Inno Deep Research in Claude Code?

Run `npx skills add LigphiDonk/Oh-my--paper --skill inno-deep-research -a claude-code`. Or copy the skill folder (skills/inno-deep-research in LigphiDonk/Oh-my--paper) into .claude/skills/inno-deep-research in your project. Claude Code loads it when a task matches its description.

How do I install Inno Deep Research in Codex?

Run `npx skills add LigphiDonk/Oh-my--paper --skill inno-deep-research -a codex`. Or copy the skill folder (skills/inno-deep-research in LigphiDonk/Oh-my--paper) into .agents/skills/inno-deep-research in your project. Codex loads it when a task matches its description.

Can I use Inno Deep Research in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add LigphiDonk/Oh-my--paper --skill inno-deep-research -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/inno-deep-research, .gemini/skills/inno-deep-research, .github/skills/inno-deep-research and .opencode/skills/inno-deep-research in your project.

What does Inno Deep Research need to run?

SKILL.md names no scripts, command-line tools or credentials: Inno Deep Research is instructions for the agent only.

Does Inno Deep Research access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Inno Deep Research safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Inno Deep Research use?

Inno Deep Research is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Inno Deep Research use?

About 2.2k tokens (SKILL.md is roughly 8.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Inno Deep Research?

Skills that share tags, products or a category with Inno Deep Research: GitHub Deep Research (bytedance/deer-flow, 84k stars), Deep Research Workflow (TokenRhythm/opensquilla, 7.1k stars), Deep Research (sanjay3290/ai-skills, 432 stars) and Horizontal-Vertical Deep Research (KKKKhazix/khazix-skills, 21k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Inno Deep Research?

LigphiDonk (a GitHub user) maintains it in LigphiDonk/Oh-my--paper, which has 739 GitHub stars. The repository holds 27 skills in this directory. The repository was last updated on April 15, 2026.

Source: LigphiDonk/Oh-my--paper on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.