Abstract Triage Log: Honest Literature Reading Notes

Start here

Copy the complete prompt (it is appended below this guide) and paste it into an ordinary AI chat that accepts text. Immediately after the prompt, paste your own list on the next line: a comma- or semicolon-separated set of entries, each ideally containing author-year or citation key, title, venue, year, abstract text, and optionally a URL/DOI plus your one-line reason for interest. If you have a research question, state it; if not, the prompt uses [WORKING QUESTION] and flags it as unset.

You need nothing else: no terminal, no account setup, no API key. Paste, send, read the reply.

How to check the output

• Every table cell should trace to words you pasted, or say UNKNOWN. Scan for any number, sample size or venue you did not supply.
• Findings must read as claimed, never verified.
• The shortlist and next actions must match the Relevance and Evidence status columns.
• If your working question was unset, the reply must say so.

If a field is missing from your entry, leave it out rather than guessing; the prompt marks gaps as UNKNOWN. Longer abstracts improve the Stated method and Claimed finding columns, but the log still describes only the abstract.

Introduction

Cataloging abstracts you have collected is different from reading papers. This prompt builds an honest triage log: it records what each abstract states, what the abstract does not tell you, and which entries deserve a full read first. It separates what an abstract asserts from what a reader might mistake for established fact. Generic AI summaries often blur that line; a reader can use this structure to keep that boundary clear.

Permissions and limits

• Suitable input: your own abstract list, your own notes, or public metadata you copy in.
• Avoid pasting confidential or unpublished manuscripts, personal data, or content you lack the right to share.
• The chat only organizes what you paste. It does not search databases, run queries, retrieve papers, or send anything.
• Findings stay labeled as claims; factual verification needs the full text.
• Fictional example: a made-up entry "Kim 2021; Abstract: survey of 214 remote knowledge workers" would be logged as Abstract-only with its response rate listed as missing.

FAQ

Can I paste fewer fields per entry? Yes. Missing title, venue or abstract fields are recorded as UNKNOWN and grouped in the Data-Gaps note so you can chase the metadata later.

Does the log judge paper quality? No. The shortlist is a provisional triage tied to your working question, not a quality rating. Citation counts and prestige are excluded.

Verification note

Source reviewed; runtime not tested. The prompt text and reference were inspected; no live run was performed.

Complete reusable prompt

You are helping me organize a literature-reading log from abstracts I paste in. I have NOT read the full papers. Your job is to build a structured, honest log I can use to triage what to read next, not to summarize papers as if abstracts were the complete text.

INPUT I will paste below a comma-or-semicolon-separated list of entries. Each entry may include: citation key or author-year, title, source or venue, year, abstract text, and optionally a URL or DOI and my own one-line reason for interest. Some fields will be missing. Do not fill gaps with guesses; mark them UNKNOWN.

MY GOAL is to answer: which abstracts actually address my question, which only seem to, and which I should read in full first. State my research question if I give it; otherwise use the working question '[WORKING QUESTION]' and flag that it is unset.

TASK

1. For each entry, output a row in a Markdown table with these columns exactly:
   • Key (use my citation key or a short author-year label you build from the title; if neither exists, use ENTRY-n)
   • Stated aim (one sentence, only what the abstract says)
   • Stated method (only what the abstract states; UNKNOWN if absent)
   • Claimed finding (only what the abstract asserts; mark as claimed, not verified)
   • Relevance to working question (High, Medium, Low, Unclear, with a one-clause reason)
   • Evidence status (Abstract-only; Full text needed; Field/definition ambiguous)
   • What the abstract does NOT tell me (specific missing inputs: sample, setting, measurement, comparison, limitations)
   • Next action (Read full text first / Skim methods / Defer / Verify citation)
2. After the table, add a SHORTLIST of the three entries most worth reading first, with a one-sentence justification each tied to the working question, and label the ranking as a provisional triage, not a quality judgment.
3. Add a CLAIMS-TO-VERIFY list of any statement that a reader might mistakenly treat as established fact but that only an abstract supports. For each, name what evidence in the full paper would settle it.
4. Add an OPEN QUESTIONS block listing what the batch as a whole cannot answer and what input I would need to supply (e.g., full texts, a numeric extract, a comparison table).
5. Add a DATA-GAPS note listing every UNKNOWN field across entries so I can chase missing metadata.

RULES

• Never state or imply that you read the full papers, ran a search, or accessed a database. You only organize what I pasted.
• Do not add papers, citations, numbers, or findings that are not in my input.
• If an abstract is ambiguous about whether a result is a finding or a hypothesis, mark it ambiguous and explain in one clause.
• Keep language plain and non-promotional; no impact-factor, popularity, or citation-count claims.
• If two entries look like the same work (preprint and published version), flag the possible duplicate and do not merge them.
• Output must be self-contained text I can paste into my notes. Do not schedule, send, or store anything.

REVIEW CHECKS before you finish:

• Does every table cell trace to words I supplied, or to UNKNOWN?
• Is every finding labeled as claimed rather than verified?
• Did you avoid ranking by perceived prestige?
• Are the shortlist and next actions consistent with the Relevance and Evidence status columns?
• If the working question was unset, did you say so clearly?

BOUNDARY: You are drafting an organizing log for me to review and act on; you are not performing research, retrieving sources, or making decisions for me.

FICTIONAL EXAMPLE INPUT (labelled): Working question: 'How do remote teams maintain informal knowledge sharing?' Entry A: 'Kim 2021; Informal knowledge flows in distributed teams; Journal of Org Work; 2021; Abstract: We survey 214 remote knowledge workers and report that ad hoc chat use correlates with perceived team memory. No sample breakdown or response rate given.' Entry B: 'Untitled preprint; no year; Abstract mentions that shared documents may substitute for hallway conversation; no method stated; no sample.'

ILLUSTRATIVE OUTPUT SHAPE (not real data): a table row for Entry A with Stated method 'survey of 214 remote knowledge workers', Claimed finding 'ad hoc chat use correlates with perceived team memory', Evidence status 'Abstract-only', 'What the abstract does NOT tell me' listing response rate and sample breakdown, and Next action 'Skim methods'; a row for Entry B with UNKNOWN fields and Next action 'Verify citation'; then a Shortlist, Claims-to-Verify, Open Questions and Data-Gaps section.

PASS/FAIL CHECKS against the fictional example:

• PASS if Entry A's row labels the correlation as claimed and lists response rate as missing.
• PASS if Entry B is marked UNKNOWN/ambiguous rather than given an invented method.
• FAIL if any row invents a sample size, venue, or finding.
• FAIL if the shortlist implies a paper was read in full.

References and reuse

• ChatGPT release notes · Reviewed 2026-10-04

Original TokRepo prompt · CC BY 4.0. Reference documents retain their own rights.