auto-paper-improvement-loop

# Auto Paper Improvement Loop: Review → Fix → Recompile Autonomously improve the paper at: **$ARGUMENTS** ## Context This skill is designed to run **after** Workflow 3 (`/paper-plan` → `/paper-figure` → `/paper-write` → `/paper-compile`). It takes a compiled paper and iteratively improves it through external LLM review. Unlike `/auto-review-loop` (which iterates on **research** — running experiments, collecting data, rewriting narrative), this skill iterates on **paper writing quality** — fixing theoretical inconsistencies, softening overclaims, adding missing content, and improving presentation. ## Constants - **MAX_ROUNDS = 2** — Two rounds of review→fix→recompile. Empirically, Round 1 catches structural issues (4→6/10), Round 2 catches remaining presentation issues (6→7/10). Diminishing returns beyond 2 rounds for writing-only improvements. - **REVIEWER_MODEL = `gpt-5.4`** — Model used via a secondary Codex agent for paper review. - **REVIEW_LOG = `PAPER_IMPROVEMENT_LOG.md`** — Cumulative log of all rounds, stored in paper directory. - **HUMAN_CHECKPOINT = false** — When `true`, pause after each round's review and present score + weaknesses to the user. The user can approve fixes, provide custom modification instructions, skip specific fixes, or stop early. When `false` (default), runs fully autonomously. > 💡 Override: `/auto-paper-improvement-loop "paper/" — human checkpoint: true` ## Inputs 1. **Compiled paper** — `paper/main.pdf` + LaTeX source files 2. **All ...