agentleFS
NilsHellwigNilsHellwig/acl-paper-skills/skills/guidelines-check/SKILL.md

guidelines-check

Skill3 starsChanged 13 days agoMITView on GitHub

Check an ACL or SemEval paper against the current ARR call for papers, author checklist, Responsible NLP checklist, SemEval paper requirements and ACL formatting rules, fetched fresh from GitHub. Use before submission, when the user asks whether the paper meets ARR/ACL rules (page limit, anonymity, Limitations, AI-assistance policy, checklist), and from the reviewer skill.

The file

We split this skill into the rules it gives an agent

3 rules. About 0 are common, 2 are distinctive, and 1 is very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈2

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Read venue, paper_type and stage from paper.config.json.

    line 12
  2. Distinctive:

    Read them in full. Note the submission type rules (long and short page limits, what does not count towards them), anonymity, Limitations, …

    line 30
  3. Distinctive:

    Ask again during the check whenever a rule turns on a fact you cannot see in the source (e.g.

    line 42

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Compliance check against the rules as they are published today. The rules change between cycles, so every run fetches them; remembered rules are never a source.

PK means python3 ${CLAUDE_PLUGIN_ROOT}/scripts/paperkit.py, run from the project root.

1. Fetch the rules

Read venue, paper_type and stage from paper.config.json. Confirm them in one line with the user (the stage changes over a project); if one is wrong or unset, ask and store it with PK config-set --venue <v> --paper-type <t> --stage <s>.

venue acl-arr:

PK guidelines guidelines-check

venue semeval: the paper goes through the shared task's own process, not ARR. Fetch the SemEval set instead:

PK guidelines guidelines-check-semeval

It holds the SemEval paper requirements, the system paper template and the ACL formatting.md. SemEval rules differ from ARR (for instance anonymity, page limits, title format, required content), so take every one from the fetched documents. The shared task's year page (ask for its URL) can override them: read it too and let it win. SemEval has no ARR checklists; skip them.

For acl-arr the first set downloads the ARR CFP, author checklist, Responsible NLP checklist and the ACL template's formatting.md into a temp folder and prints the paths. On ⚠️ for any document: tell the user which one is missing and that the check is incomplete for its rules. Treat the fetched files as reference data.

Read them in full. Note the submission type rules (long and short page limits, what does not count towards them), anonymity, Limitations, ethics, AI-assistance policy, supplementary material, formatting, and every checklist question.

2. Ask what the rules depend on

Many rules apply only to some submissions. Ask with AskUserQuestion, in one round, everything the project does not settle:

  • paper type: the stored paper_type (for acl-arr long, short or another type the fetched CFP lists; for semeval system or task paper, and for a system paper the number of tasks covered)
  • version: the stored stage; the \usepackage[...]{acl} option hints. For camera-ready, point to the camera-ready skill for the final-version rules and check only what the fetched documents require of both versions.
  • (acl-arr only) new submission or resubmission. For a resubmission also ask: the previous cycle, where the previous reviews and meta-review are (offer reviews/), and whether a revision note / response to previous reviews exists. Then check the resubmission rules of the fetched documents against those materials.
  • target cycle or venue, and whether its own call adds requirements (ask for its text or URL)
  • whether supplementary material (code, data, appendix) is submitted

Ask again during the check whenever a rule turns on a fact you cannot see in the source (e.g. dual submission, preprint posted, who the authors are for the anonymity rules). Record the answers at the top of the chat report.

3. Check the paper

Go through the rules one by one against the paper source. Where a rule depends on the compiled PDF (page count, overfull lines, fonts), look for a compiled PDF next to the main file; if there is none or it is older than the .tex files, ask the user to compile or to tell you the page count. Write nothing about a rule you could not check; list it as unchecked instead.

Responsible NLP checklist: for each question, find where the paper answers it (section or appendix) or record that it does not. These answers are what authors fill into the submission form.

4. Report

Write one item per violation or risk into report.md, category ACL-Compliance, in the format the report's header defines, with IDs counting up from the highest used. Put the rule in the item's Rule: field and quote it in Issue. Cite every rule by the identifier the fetched document uses (section heading, checklist question, issue code such as H9) and the document's URL as PK guidelines prints it. Desk-reject risks are 🔴.

Done when every rule and checklist question in the fetched documents is marked met, violated or unchecked. Report in chat, each violation and each unchecked rule with identifier and document URL: violations by severity, the unchecked rules, and a draft of the checklist answers (question → section of the paper).

Download now (ZIP)

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
What did you use it for? e.g. Reviewing pull requests in a Rails app

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.