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Three modes for CS-conference papers (CVPR/ICCV/ECCV vision, ACL/EMNLP/NAACL NLP, ICLR/NeurIPS/ICML/AAAI ML). DIRECT-EDIT mode (common): the user describes a change in Chinese or English and the manuscript (LaTeX or Markdown) is edited directly through a CS-venue writing toolkit with author sign-off (use for 改这段 / 把中文想法写成 latex / polish / de-AI / translate / compress a passage). REVIEW mode (occasional, pre-submission): harden the paper through an adversarial courtroom review engine (N holistic
Passed 14 of 19 test cases with the skill, and 3 of 19 without it.
and 15 more in the full report
13 fixed3 passed either way6 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 13 test cases the skill fixed. Same model, same prompt, with and without the skill.
At the conclusion of a review round, which workflow step is responsible for reconciling open questions against applied edits using passage IDs and emitting convergence counts?
| Checked | Without skill | With skill |
|---|---|---|
| Identifies the clerk step as responsible for round reconciliation and convergence reporting. | Missed | Passed |
The instructions your model reads when the skill loads.
PaperJury edits and hardens any CS-conference paper. It runs in
three modes. In direct-edit mode (the common case) the user describes a change
in Chinese or English and the LaTeX is edited directly through a CS-venue writing
toolkit, with author sign-off. In review mode (occasional, pre-submission) it
exposes the manuscript to a harsh, multi-perspective courtroom review engine that
adjudicates each issue (N holistic domain reviewers -> contestability routing ->
two-sided trial -> three-way verdict, with a polish track and a clerk-converged
multi-round loop), gates every change behind consensus, and tracks issues in a durable
ledger. In auto mode (unattended, opt-in via /goal) it runs that same engine
toward a verifiable goal, applying safe fixes under a drift-bounded policy and
queueing the risky ones for one human pass on return. All modes share the same
writing toolkit, hard rules, ledger, and author sign-off (auto via up-front policy
sign-off plus the queue, see hard rule 1).
This skill is fully generic. It ships no hardcoded paths, no project files, and no embedded paper. Everything specific to a given paper (where the manuscript is, the venue, who signs off, the house style) is resolved at runtime or supplied by a config the project owns. The skill itself is the backbone; any concrete paper is just an instantiation of it.
Scope: CS conferences only. Three venue families, each with its own style profile:
Three modes, one skill. Pick by what the user is asking for:
references/review-engine-v3.md)./goal (or config mode: auto)
to run the review-revise loop AFK toward a verifiable goal. Establish the spinetest cases passed, vs 3 / 19 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.