auto-paper-improvement-looplisted

ultrathink # 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 = `o3`** — Model used via Codex MCP for paper review. - **REVIEWER_BIAS_GUARD = true** — When `true`, every review round uses a fresh `mcp__codex__codex` thread with no prior review context. Never use `mcp__codex__codex-reply` for review rounds. Set to `false` only for deliberate debugging of the legacy behavior. **Empirical evidence (April 2026):** running the same paper with `codex-reply` + "since last round we did X" prompts inflated scores from real 3/10 → fake 8/10 across 5 rounds; switching to fresh threads recovered the true 3/10 assessment. - **REVIEW_LOG = `PAPER_IMPROVEMENT_LOG.md`** — Cumul