Check Originality logo

Check Originality

Community
ShaishavMaisuria
check-originality

Checks a draft for plagiarism, self-plagiarism, text recycling, and uncited near-quotes using several detection methods, and reports overlapping passages so the author can fix them before reviewers or an integrity check do. Use when a researcher says "check for plagiarism", "plagiarism check", "did I copy too much", "self-plagiarism", "text recycling", "am I reusing too much of my own paper", "check originality", "is this too close to the source", or "did I paraphrase closely enough". Compares the draft against sources the user provides (their own prior papers, co-author drafts, suspected sources, or papers fetched on demand), detects internal duplication, and surfaces distinctive phrases to search externally. Honest about scope - it is not iThenticate/Turnitin and has no private publisher corpus; it catches overlap against given sources and publicly findable phrases. Trigger words - plagiarism, self-plagiarism, text recycling, originality, copied, overlap, too close to source, duplicate text.

Overview

PublisherShaishavMaisuria
Repositoryresearch-paper-lifecycle-skills
Skill namecheck-originality
Stars
59
Forks
22
Bundled files
2
LicenseApache-2.0
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.

  • 2 bundled files

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

  • Open source

    Published by ShaishavMaisuria on GitHub. Read the source before you install it.

Installation

Install the Check Originality 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/ShaishavMaisuria/research-paper-lifecycle-skills/tree/main/skills/check-originality
  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/ShaishavMaisuria/research-paper-lifecycle-skills.git /tmp/research-paper-lifecycle-skills
mkdir -p .claude/skills
cp -r /tmp/research-paper-lifecycle-skills/skills/check-originality .claude/skills/check-originality
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Check Originality 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 Check Originality 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 Check Originality 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.

Check Originality

Multi-method originality check that catches the overlap which actually gets papers desk-rejected or retracted — before an editor's integrity scan does.

Read this honestly and tell the user: this is not iThenticate or Turnitin. It has no access to any private publisher corpus, so it cannot guarantee a passage is original against all published literature. What it does reliably is detect overlap against sources you can name or fetch, internal text recycling, and distinctive phrases that are publicly searchable. For a journal's official originality report you still need the publisher's tool — this gets your draft clean first.

When to use

  • Before submission, to catch accidental copy-paste and close paraphrase.
  • When reusing your own prior work (text recycling / self-plagiarism is a real violation at most venues even though it's "your" text).
  • When a co-authored draft may contain a collaborator's verbatim text from elsewhere.
  • After heavy AI drafting, to confirm nothing was reproduced verbatim from a source.

The detection methods (run several — that's what "catch it properly" means)

See references/detection-methods.md for the full method and thresholds.

  1. Source overlap — shingle (k-gram) comparison against sources the user provides or that fetch-paper pulls (open-access only). Reports matched passages + overlap %.
  2. Self-plagiarism / recycling — near-duplicate passages against the author's own prior papers, and internal duplication within the draft.
  3. Quote & paraphrase integrity — verbatim spans that lack quotation marks or a citation; paraphrases that stay too close to the source's wording.
  4. Distinctive-phrase external search — pull the draft's most distinctive long phrases and search the web / Semantic Scholar for verbatim matches the local check can't see.
  5. Common-knowledge vs needs-citation — flag factual claims presented without a citation that likely need one (hand off specifics to verify-citations).

Process

  1. Gather comparison sources. Ask the user for: their own prior papers (for self-plagiarism), any suspected sources, and the paper's own cited references (fetch the open-access ones with fetch-paper). More sources = a more meaningful check; say so.
  2. Run source + self overlap:
    python3 scripts/overlap_check.py --draft paper.tex --against prior1.tex prior2.tex source.txt --self --distinctive 15
    It prints flagged sources (overlap %), the matched passages, internal near-duplicates, and distinctive phrases. Exit code 2 if anything is flagged.
  3. External pass. Take the emitted distinctive phrases and search them (web + Semantic Scholar via find-papers) for verbatim hits the local pass couldn't see. Record any matches.
  4. Quote/paraphrase review. For each flagged passage, decide: is it a legitimate quote (then it needs quotation marks + citation), an over-close paraphrase (rewrite in the author's own words), or copied (remove/rewrite + cite). Self-overlap with prior work → flag as recycling and advise disclosure or rewrite.
  5. Report to paper-workspace/review/originality-report.md in the user's paper workspace: each finding with source, the overlapping text, severity, and the fix — plus the explicit scope caveat.

Output

An originality report listing, per finding: the source, the overlapping passage, overlap %, type (external copy / self-recycle / unquoted / close-paraphrase), severity, and the recommended fix. Always includes the scope/limitations note and a reminder that the publisher's own tool is still authoritative.

Guardrails

  • Never claim a clean result means the paper is plagiarism-free — only that no overlap was found against the sources checked. State the limitation every time.
  • Comparison sources are processed transiently; never bundle or commit third-party paper text (see fetch-paper). Only the user's own papers and open-access sources are fetched.
  • Never rewrite a flagged passage to merely evade detection while keeping the copied idea uncited — the fix is proper quotation/citation or genuine rephrasing, and surfacing it to the author.
  • Self-overlap with the author's own work is reported as an ethics/recycling issue, not silently passed.

Memory

Uses the shared .paper-memory/ convention (full spec: paper-memory-convention.md).

  • At start: read lessons.md for prior originality flags so repeat offenders (a section the author keeps recycling) are checked first.
  • At end: append durable findings — date · check-originality · <scope> · finding · fix — after deduping. A passage recycled across multiple drafts is recurring.
  • Create .paper-memory/ on demand; it is local-only, never uploaded.

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 Check Originality AI skill do?

Checks a draft for plagiarism, self-plagiarism, text recycling, and uncited near-quotes using several detection methods, and reports overlapping passages so the author can fix them before reviewers or an integrity check do. Use when a researcher says "check for plagiarism", "plagiarism check", "did I copy too much", "self-plagiarism", "text recycling", "am I reusing too much of my own paper", "check originality", "is this too close to the source", or "did I paraphrase closely enough". Compares the draft against sources the user provides (their own prior papers, co-author drafts, suspected s...

Why use Check Originality on TypingMind?

Because you install it once and use it with any model. Check Originality 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 Check Originality in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ShaishavMaisuria/research-paper-lifecycle-skills/tree/main/skills/check-originality. 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 Check Originality?

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 Check Originality?

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

Is the Check Originality AI skill free?

Yes. It is published on GitHub by ShaishavMaisuria 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.

View all

Set up your own AI workspace now

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