paper-verify-before-handoff

paper-verify-before-handoff is a skill for Claude Code, Codex from Lambenthan/paper-discipline-skills. It costs 190 tokens per session (2,172 once invoked), scanned A, original, MIT.

A pre-delivery checklist for research-paper work that checks the result before it is declared finished or submitted.

In plain words
What is it for?
It helps review citations, numbers, figure and section links, word limits, unfinished notes, signs of machine-written prose, argument consistency, and the final change summary.
Why use it?
It catches inconsistent terms, missing references, incorrect data, broken cross-references, formatting problems, leftover placeholders, and unsupported claims.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions CLAUDE.md; mentions Claude Code.

Good fit It helps review citations, numbers, figure and section links, word limits, unfinished notes, signs of machine-written prose, argument consistency, and the final change summary.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/lambenthan/paper-discipline-skills/paper-verify-before-handoff
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add Lambenthan/paper-discipline-skills --skill paper-verify-before-handoff
Clone the repo
git clone --depth 1 https://github.com/Lambenthan/paper-discipline-skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for paper-verify-before-handoff

README.md
[![agentmods](https://agentmods.dev/badge/skills/lambenthan/paper-discipline-skills/paper-verify-before-handoff/github.svg)](https://agentmods.dev/skills/lambenthan/paper-discipline-skills/paper-verify-before-handoff)
Your own site
<a href="https://agentmods.dev/skills/lambenthan/paper-discipline-skills/paper-verify-before-handoff"><img src="https://agentmods.dev/badge/skills/lambenthan/paper-discipline-skills/paper-verify-before-handoff/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for paper-verify-before-handoff

Your own site · 80×15
<a href="https://agentmods.dev/skills/lambenthan/paper-discipline-skills/paper-verify-before-handoff"><img src="https://agentmods.dev/badge/skills/lambenthan/paper-discipline-skills/paper-verify-before-handoff.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 190 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,172 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00190 $0.02172
Opus 5 $0.00095 $0.01086
Sonnet 5 $0.00038 $0.00434
Haiku 4.5 $0.00019 $0.00217

Measured 12d ago against content hash 4ca5bae3a440, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

paper-verify-before-handoff scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

paper-verify-before-handoff/SKILL.md · 146 lines

How it starts

The opening of the file, as written. The whole thing — 146 lines — stays where its author put it; the contents beside it link to each section on GitHub.

paper-verify-before-handoff:交付前最后一道闸

核心理念

AI 写得太流畅会让人放松警惕。最致命的错误不是写错,是**"看起来对了所以不查了"**。 书里第 14 章的核心:对结果负责的永远是你,不是 AI——所以 AI 必须替你建一道交付闸。

完成 = 通过检查清单,不是"AI 觉得做完了"。


触发条件

满足任一条 → 触发:

  • 你即将在回复里写出"改完了"、"完成了"、"已经处理好"、"可以提交"、"可以发了"
  • 用户问「是不是可以了」、「还有什么要检查的吗」、「能发给导师吗」
  • 你即将说「这就是最终版本」
  • 一个章节 / 整篇论文的修改任务即将关闭

强制流程

你即将宣告"完成"
        │
        ▼
立即停下,不要发出"完成"的消息
        │
        ▼
按下方"硬检查清单"逐条核
        │
        ▼
所有项 PASS → 把检查报告作为完成消息的一部分发出
任何一项 FAIL → 列出问题,告诉用户"还差这几条,先不能算完"

硬检查清单(必查 10 项)

# 怎么查
1 术语一致性 grep 本次涉及的所有保护术语,确认没出现替换
2 引用完整性 所有 \cite{} / [X] 标号在参考文献里都能查到,反之亦然
3 数据正确 所有改动里的数字、百分比、年份与原始数据 / 上文一致
4 图表编号 图 1、图 2... 连续,文中"图 X"指向的图编号确实存在
5 内部交叉引用 "如 §3.2 所述"、"见表 4",引用的目标确实存在
6 字数 / 格式合规 满足 CLAUDE.md 里声明的字数 / 格式要求
7 Todo 残留 grep TODO / FIXME / xxx / ?? 等占位符确认全部清掉
8 AIGC pattern(如本轮涉及文段改写 / 润色 / 通顺化) chinese-de-aigc 五维自评,加权总分 ≥ 42 分;任何高严重度 AI 痕迹(四字套话、显性连接词、绝对化断言、隐藏被动)已修正
9 论证一致性(如本轮改动了核心声明) paper-logical-consistency 扫描全文:本次改动涉及的研究问题 / 核心论点 / 假设 / 因果声明 / 边界条件 / 主要结论,在其他章节的出现都已逐处与用户确认(同步修改 / 保留原样)
10 改动概要 用一句话复述改了什么、未改什么,让用户能秒判对错

第 8 项的"涉及文段改写"判定:本轮有任何 Edit / Write 改动了文段(不是只改格式 / 引用 / 编号 / 图表)→ 必须查。 第 9 项的"涉及核心声明"判定:本轮改动是否触及研究问题 / 核心论点 / 主要结论 / 方法边界 / 对已有研究的态度。改动了 → 必须跑;纯格式 / 引用 / 数据修订则跳过。 不是"觉得改得不多就跳过"——只要符合判定就要跑。


标准交付消息模板

改完了。交付前自查结果:

✅ 术语一致:[检查的术语列表],无替换 ✅ 引用完整:新增 X 条引用都在参考文献里,无悬挂 ✅ 数据:[列出涉及的关键数字],与原始一致 ✅ 图表编号:图 X、表 Y 编号连续,文中引用全部命中 ✅ 交叉引用:[列出本次涉及的 §X.X / 表 X / 图 X],全部命中 ✅ 字数 / 格式:[当前字数 / 限制] · [格式状态] ✅ Todo:grep 无残留 ✅ AIGC pattern:chinese-de-aigc 五维评分 [具体分](≥ 42 通过);高严重度痕迹 [N] 处已修正 / 本轮未涉及文段改写,跳过 ✅ 论证一致:本次改动的核心声明 [列出] 在 §X.X / §Y.Y / §Z.Z 也出现,已逐处与用户确认 / 本轮未改动核心声明,跳过

本次改动概要:[一句话复述] 未触及部分:[一句话明示]

现在可以发给导师 / 提交了。


❌ 反例(书 §14.2)

用户:"改完第三章给我发一份。"

错误做法:AI 改完,回:"改完了,文件已保存。"

  • 用户直接发给导师
  • 导师两小时后回:"你这个引用 [12] 在参考文献里没有"
  • 用户回头查 → 发现还有三处类似问题

Read the full file on GitHub · 146 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 12d ago First seen · 146 lines · 190 tokens per session scan A 4ca5bae3a440

Subscribe to this mod's changes

paper-verify-before-handoff is a skill published in the GitHub repository Lambenthan/paper-discipline-skills (19 stars, last pushed 4mo ago), licensed MIT. It adds 190 tokens to every session and 2,172 once invoked, about $0.0010 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

paper-writer

Medical/scientific paper writing workflow skill. Manages the full pipeline from literature search to submission-ready manuscript. Creates and manages a project directory with IMRAD-format section files, literature matrix, reference management, and quality checklists. Supports both English and Japanese papers.…

kgraph57/paper-writer-skill · 106 tokens

food-research

Run a comprehensive, multi-source literature and evidence-synthesis workflow for food & nutrition science. Use when the user wants to research a food/nutrition topic in depth, do a literature review, build an evidence brief, screen and synthesize many sources, verify citations, or scope a systematic review.…

PangenomeAI/academic-skills-food-nutrition · 154 tokens

food-paper

Multi-subagent manuscript system for food & nutrition science covering the whole research process: understand the field, frame research questions, curate and analyze data, run statistics, build figures and tables, construct the discussion, draft, polish, and self-review — journal-aware throughout. Includes a…

PangenomeAI/academic-skills-food-nutrition · 180 tokens

food-pipeline

Master orchestrator for the whole food & nutrition research-to-publication workflow. Coordinates the specialist skills — each with its own subagent set — into one governed path: journal selection, research (food-research / food-deep-research), writing & analysis (food-paper), figures (food-figure), peer review…

PangenomeAI/academic-skills-food-nutrition · 137 tokens

food-deep-research

General-purpose deep research that produces a fully written, source-validated literature review on any question: scope it, design the method, discover and screen sources by journal ranking, validate every source, extract and verify evidence, synthesize, stress-test, then write and format the review (APA 7.0 by…

PangenomeAI/academic-skills-food-nutrition · 166 tokens

food-figure

Comprehensive figure system for food & nutrition manuscripts: analyzes the user's data, recommends the best figure(s) to make, then produces submission-grade graphics in Python or R at the target journal's spec. Handles all common scientific figure types (bar/box/violin, line/kinetic, scatter/regression, Bland–Altman…

PangenomeAI/academic-skills-food-nutrition · 218 tokens