cite-check
Skill0 starsChanged 3 months agoMITView on GitHub
Check whether each citation in a text actually supports the sentence it is attached to, and flag identifiers that do not resolve.
6 other projects use a version of this.
Adopted by
Most recently taken up by
- Walsworth-Group/physkittheir own version, first seen Nov 8, 2026
- enstw/thesisbug2their own version, first seen Nov 8, 2026
- zedxter/utility-belttheir own version, first seen Nov 1, 2026
- williamhorschak-dev/wisconsin-legal-ai-skillstheir own version, first seen Oct 25, 2026
- Sprintlaw/legal-skillstheir own version, first seen Oct 17, 2026
- opelpleple/meta-skillstheir own version, first seen Oct 11, 2026
Other versions6 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 6
- Walsworth-Group/physkit★ 7same name
- zedxter/utility-belt★ 4same name
- williamhorschak-dev/wisconsin-legal-ai-skills★ 2same name
- enstw/thesisbug2★ 0same name
- opelpleple/meta-skills★ 0same name
- Sprintlaw/legal-skills★ 0same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository4 other files it gives its agents.
- as-ofSkill
- chatSkill
- evidence-checkSkill
- groundSkill
The file
We split this skill into the rules it gives an agent
1 rule. 0 are common, 1 is distinctive, and 0 are very specific to this project.
0
Common
Most of the 6 edited versions we read keep these.
1
Distinctive
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 33
Look for the paper in the returned bundle by hard id, then compare what the retrieved record says against what the sentence claims from it.
“Common” is measured: kept by at least 6 in 10 of the 6 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Check citations against what they are cited for
Target: $ARGUMENTS (a file, a passage, or the document in context).
A citation fails in three distinct ways, and they need different handling:
- It does not exist. The identifier resolves to nothing, or to a different paper than the one named. This is the failure mode that matters most when text was drafted with a language model, since plausible-looking identifiers are easy to generate.
- It exists but does not say that. Real paper, wrong support. Often it is adjacent work, a review citing the actual source, or the right group's different study.
- It exists and is about the right thing, but does not carry the weight. A mechanism paper cited for a clinical outcome, a preprint cited as settled, an animal result cited for a human claim, a single arm cited as a comparison.
What to do
- Extract every citation and the specific sentence each one is attached to.
- For each, run
zetesis_evidencewithas_ofset to the cited year and three to six short queries, in this order. Titles, author lists, and study-design phrases retrieve commentary instead of the paper, so never pass them.- The identifier alone, bare:
10.1056/NEJMoa2034577, or33301246. NoPMID:ordoi:prefix. This is the highest-yield query and usually resolves on its own. - The entity alone: the drug, compound code, gene, or model. One or two words.
- That entity plus at most two words naming the outcome.
- Optionally the disease or endpoint alone.
- The identifier alone, bare:
- Look for the paper in the returned bundle by hard id, then compare what the retrieved record says against what the sentence claims from it.
- Classify: resolves and supports, resolves but does not support the sentence, resolves but is too weak for the claim, or could not be retrieved.
Reporting
One line per citation, grouped by classification, worst first. For anything that is not a clean pass, quote the sentence and say in one line what the source actually supports.
Be careful with "could not be retrieved". Use it only after both the bare-identifier query and the entity-anchored queries have missed. It means the search did not surface it, which is not the same as the paper not existing: coverage is not complete, older and non-indexed work is patchy, and a book or a thesis will usually not appear. Say "not retrieved" and let the author confirm, rather than declaring a citation fabricated. If the bundle reports that retrieval was degraded for a source, withhold the classification for that citation instead of recording a failure. Be direct about the ones you did confirm are wrong.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

