Check an AI summary of a research paper against the original
KINDA — AI can help, with a person in the loop.
1 method on the page: 1 agent.
Methods
Read the paper, check the citation details and methods, then judge the summary yourself
Steps
- Read the abstract, and ideally the full paper. Open the original work to confirm that it matches the topic and claims made by the AI tool.
- Check that the bibliographic details (author, title, journal, year and volume/issue) match with the original record.
- Look for important details about study design and methods that the AI may have skipped or simplified.
- Check whether the AI summary reflects the full paper and use your own judgement.
- Note: Steps quoted from Bodleian Libraries, University of Oxford (CC BY 4.0). The final check is your own reading of the paper.
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--- name: "check-ai-paper-summary-against-source-method" description: "Use when you need to Check an AI summary of a research paper against the original. Read the paper, check the citation details and methods, then judge the summary yourself" --- # Read the paper, check the citation details and methods, then judge the summary yourself Job: [Check an AI summary of a research paper against the original](https://aiagents.org/canai/check-ai-paper-summary-against-source) ## Need - AI agent ## Steps 1. Read the abstract, and ideally the full paper. Open the original work to confirm that it matches the topic and claims made by the AI tool. 2. Check that the bibliographic details (author, title, journal, year and volume/issue) match with the original record. 3. Look for important details about study design and methods that the AI may have skipped or simplified. 4. Check whether the AI summary reflects the full paper and use your own judgement. 5. Note: Steps quoted from Bodleian Libraries, University of Oxford (CC BY 4.0). The final check is your own reading of the paper. ## Credit Method author Bodleian Libraries, University of Oxford (CC BY 4.0) Source: https://libguides.bodleian.ox.ac.uk/ai-for-literature-searching/evaluating-ai-references
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How you would do this use case, in plain words. Anyone can post.
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GET /api/jobs/check-ai-paper-summary-against-source - Schema:
GET /api/jobs/schema - Add a method:
POST /api/jobs/method— same fields as the form. No API key yet.
A bad request returns JSON like {"error":"Method description is required"} with status 400.
| Field | What it is |
|---|---|
jobId | This use case. Review queue uses useCaseTitle + email instead. |
summary | Method description. Shown on the card. Also accepts title. |
products | Optional. Array of { name, url }. Legacy: tools. |
prompts | Optional. Array of prompt strings. Legacy: one prompt string. |
skills | Optional. Array of { text, url }. Legacy: skill + skillUrl. |
authorName | Author name. Legacy live field: postedBy. |
author | Optional 𝕏 handle. Legacy live field: creditHandle. |
parts | Optional. Inferred from products, prompts, and skills if omitted.standalone-product, ai-agent, ai-tool, skill, prompt. Do not send a prompt/product/agent/skill radio. |
{
"jobId": "check-ai-paper-summary-against-source",
"summary": "Turns a Zoom recording into notes and action items with owners",
"products": [
{
"name": "Claude",
"url": "https://claude.ai"
}
],
"prompts": [
"Turn this transcript into notes and action items with owners."
],
"skills": [
{
"text": "Watch a folder. When a transcript lands, write notes with owners.",
"url": "https://example.com/zoom-notes.md"
}
],
"authorName": "Alex Rivera",
"author": "@handle"
}