presentation-signals

Presentation Signals — the surface tells (auxiliary, never a verdict)

Run surface signal checks for: $ARGUMENTS (requires claims.json from /evidence-ledger). Emit span-anchored presentation-signals.findings.json. This skill computes no verdict.

⚠️ This skill is deliberately weak by design. A polished paper can be fraudulent and a rough paper can be honest, so surface signals must never drive a verdict. Everything here is emitted under skill presentation-signals, which the adjudicator caps at minor (SURFACE_ONLY_SKILLS + SURFACE_PATTERNS in tools/adjudicate_findings.py) — at most SOFT_FLAGS, never HARD_FLAGS. This is not an AI-text classifier; for authorship detection use a dedicated tool (Pangram / GPTZero / Binoculars). Our only job is to add "combine with the substantive findings and look closer" context. See references/hack-pattern-taxonomy.md §F.

🔒 Do not wrap this skill in /loop, /schedule, or CronCreate. It is verdict-bearing input — it proposes the surface findings the deterministic adjudicator turns into the report. Re-firing it on a wall-clock timer adds no signal: its output changes only when the paper / ledger changes, not with the clock. Schedule the external wait that precedes it — ledger built → check once. (Mirrors ARIS's external-cadence doctrine.)

Why this exists

Real reviewers notice surface tells before they read a single number — and they say so out loud: "两张表一模一样" (two tables are identical), "图还是大模型生成的" (the figure is LLM-generated), "就这还没写满9页" (couldn't even fill 9 pages), "堆砌名词吗" (just stuffing jargon?), "本文不是什么什么，而是什么什么…论文应该直接表达 做了什么" (stop hedging "this paper is not X but rather Y" — just say what you did), "摘要写的像实验分析,读不到引言" (the abstract reads like an experiment log; the introduction is unreadable). An autoresearch pipeline (or a rushed human) produces exactly these artifacts: a table copy-pasted and never updated, an oversized float to pad the page limit, a decorative generated illustration in place of a real results plot, paragraphs of generic LLM boilerplate, draft text so densely over-hedged that every sentence defends against an objection, and an abstract that dumps experiment notes instead of telling a background → contribution → evidence story.