agentleFS
JihaoXinJihaoXin/paper-machine/skills/delivery-contract/SKILL.md

delivery-contract

Skill0 starsChanged 3 months agoMITView on GitHub

The checks that decide whether a paper is finished. Use before declaring a paper done, delivering a draft, or reporting success. Replaces "the writing step returned" with evidence from the artifacts themselves.

The file

We split this skill into the rules it gives an agent

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

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈3

    Distinctive · estimate

    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
  1. Distinctive:

    Do not report success on any path that has not produced:

    line 39
  2. Distinctive:

    If a run ends without these, it failed, whatever the log says.

    line 45
  3. Distinctive:

    If an agent wrote it, the paper says so.

    line 52

≈ “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

Delivery Contract

Why control flow is not evidence

An agent pipeline reports success when its last function returns. That says nothing about whether a paper exists. Observed outcomes that all reported "done": a 12 KB PDF containing a template skeleton, a paper whose every citation rendered as ?, a full draft written with zero literature behind it because the research step had failed silently an hour earlier.

The fix is to stop asking the code whether it finished and start asking the artifacts what they are.

Run these before saying done

Each check reads the delivered files. Hard means the paper does not ship. Soft means it ships with the problem stated out loud.

CheckSeverityPasses when
PDF existshardmain.pdf is present and over ~50 KB. A smaller file is a template, not a paper.
PDF is readablehardA PDF parser can open it and extract text.
Citations resolvedhardNo ? markers in the rendered text.
References non-emptyhardThe text cites something and references.bib has entries.
AI disclosure presenthardThe paper states it was produced with AI assistance.
Figures referencedsoftEvery included figure has a \ref in the prose.
Figures not upscaledsoftNo bitmap displayed beyond its native resolution.
Page budgetsoftBody pages fit the venue limit.
Research groundedsoftA real literature survey backs the related work.
Numbers tracedsoftEvery numeric claim points at a result file.

Evidence-based done

Do not report success on any path that has not produced:

  1. a PDF over 50 KB that a parser can open,
  2. zero unresolved citations,
  3. a non-empty bibliography.

If a run ends without these, it failed, whatever the log says. Say so, say why, and say what the user can do about it. A truthful failure is worth more than a confident lie, and a user who is told "the literature step failed, so this draft has no related work" can act on it.

Disclosure

If an agent wrote it, the paper says so. This is not optional and it is increasingly a submission requirement. One line in the acknowledgements is enough:

This paper was prepared with the assistance of an AI research agent.

Two things to get right. It must survive into the rendered PDF, not just the source, so check the extracted text. And it must not leak internal machinery, tool names, stack traces or file paths into an acknowledgements section a reviewer will read.

Report the outcome honestly

State what passed and what did not:

Delivery: 8 checks passed, 1 soft violation
  page_budget: 10 pages against a 4-page budget (references span 5 pages)

Then let the user decide. Hiding a soft violation to make the summary look clean is the same instinct that produces invented numbers, just wearing better clothes.

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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.

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