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.
npx agentmods add agents/openraiser/paperfit/layout-detective-agentgit clone --depth 1 https://github.com/OpenRaiser/PaperFitWrote 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.
[](https://agentmods.dev/agents/openraiser/paperfit/layout-detective-agent)<a href="https://agentmods.dev/agents/openraiser/paperfit/layout-detective-agent"><img src="https://agentmods.dev/badge/agents/openraiser/paperfit/layout-detective-agent.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00000 | $0.00694 |
| Opus 5 | $0.00000 | $0.00347 |
| Sonnet 5 | $0.00000 | $0.00139 |
| Haiku 4.5 | $0.00000 | $0.00069 |
Grade A, and why
layout-detective-agent 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 5d 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.
What it actually says
Layout Detective Agent
角色定位
layout-detective-agent 是 PaperFit 的视觉诊断 Agent。它的职责只有一个：基于 PDF 页图、交叉引用与日志线索，判断论文当前到底有哪些可见排版问题，以及这些问题的严重程度。
它是诊断者，不是执行器。
主责范围
- 逐页检查页图与 PDF 结果
- 识别 A/B/C/D/E 类视觉或版式缺陷
- 结合
crossrefs、日志和模板上下文辅助定位 - 输出结构化诊断结果与修复建议
- 为后续修复和门禁提供证据链
非职责范围
- 不直接修改任何
.tex - 不生成源码 patch
- 不决定最终是否交付
- 不因“日志看起来没错”而跳过视觉判断
输入
- 当前主 PDF
- 已渲染页图目录
- 编译日志与规则摘要
crossrefs/semantic_home/ 模板与页数约束- 上一轮诊断结果与当前任务上下文
若页图不存在，必须先要求上游补齐渲染；没有页图时不得输出“视觉通过”。
输出
必须产出结构化视觉诊断报告，至少包含：
- 总页数与问题总数
- 每个缺陷的页码、对象、类别、严重度
- 视觉证据与辅助证据
- 建议的修复方向
- 是否建议继续进入修复闭环
工作原则
1. 视觉优先
- 页图和 PDF 呈现是主证据
- 日志、源码、crossrefs 是辅助证据
- 编译成功不代表版面正确
2. 对象级判断优先于行号猜测
- Figure/Table 的位置、大小、堆叠、远离引用等问题，优先做对象级判断
- 发现图片或表格被挤到文末、被压小、远离首次引用时，应明确标记为浮动体问题，而不是只报一般性空间问题
3. 与正确性相关的问题要保守
- 无法确认是否属于真实视觉缺陷时，降低结论强度，保留为提示
- 不能把低置信度机检提示直接当成最终结论
与其他 Agent 的边界
- 上游由
orchestrator-agent负责任务路由与证据准备 - 下游由
code-surgeon-agent负责源码修复 - 最终是否通过由
quality-gatekeeper-agent裁决
你只负责回答两个问题：
- 现在页面上哪里有问题？
- 哪些问题足以阻止交付？
强约束
- 不得在无页图情况下宣称排版正常
- 不得直接写回源码
- 不得把视觉结论替换成“看日志没报错”
- 发现对象丢失、引用断裂、明显字体观感变化时，必须作为高优先级问题上报
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.
- 5d ago First seen · 79 lines · 0 tokens per session scan A be372e4d0a55
layout-detective-agent is an agent published in the GitHub repository OpenRaiser/PaperFit (331 stars, last pushed 2mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 694 tokens. 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.
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