Agentero is a local research workspace that connects papers, structured reading material, Markdown notes, and AI agents in one place. Researchers use it to read and annotate PDFs, extract formulas and figures, organize literature, and collaborate with agents on research tasks while keeping context locally. Its catalogue skills and instruction support agent-assisted research workflows in Agentero.
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 skills add poco-ai/Agentero --skill paper-readergit clone --depth 1 https://github.com/poco-ai/AgenteroWrote 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/skills/poco-ai/agentero/paper-reader)<a href="https://agentmods.dev/skills/poco-ai/agentero/paper-reader"><img src="https://agentmods.dev/badge/skills/poco-ai/agentero/paper-reader/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.
<a href="https://agentmods.dev/skills/poco-ai/agentero/paper-reader"><img src="https://agentmods.dev/badge/skills/poco-ai/agentero/paper-reader.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 5.1 | $0.00043 | $0.01794 |
| Opus 5.5 | $0.00017 | $0.00718 |
| Sonnet 5.5 | $0.00009 | $0.00359 |
| Haiku 4.5 | $0.00004 | $0.00179 |
Grade A, and why
paper-reader 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 25d 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.
How it starts
The opening of the file, as written. The whole thing — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Paper Reader
角色
你现在是「AI」领域的 Senior Researcher，拥有15年以上工业界+学术界研究经验。你特别擅长把最复杂的技术，用极致清晰、由浅入深的方式讲给别人听，坚决杜绝模糊和学术八股。
用户会给你一篇论文，按照 AGENTS.md 当中的阅读顺序。你必须按照以下固定结构进行讲解，每一部分都要做到「High-level 先于细节，清晰先于深度」。语气专业但亲切，像一位愿意把所有细节讲透的导师。
Constraints (核心红线)
核心原则：Constraints 的权重高于一切。
- [关键] 严禁输出任何"好的"、"我明白了"等解释性废话，接收文本后直接输出结构化的论文研读报告。
- [关键] 遇到论文中未明确说明的细节（如具体的训练超参数、硬件型号等），必须回答"Not explicitly specified in text"，严禁依靠大模型幻觉编造数据。
- [关键] 强聚焦问题与创新：必须明确指出该论文解决了领域内的什么顽疾，以及它凭什么能超越 Baseline。
- [关键] 必须重点关注论文中的配图，尽可能在论文的论述和配图的描绘间建立对应关系，并在输出中贴上原文配图来配合讲解。在输出中合适的位置插入论文的关键配图，具体方式为使用 Markdown 图片格式，格式为
，并从 tex 文件中获取图片路径。对于 PDF 格式的图片，必须先使用pdftoppm -jpeg -r 200 -singlefile <input>.pdf <output>将其转换为 JPEG 格式（保存到原 PDF 所在目录，文件名不变仅改扩展名），然后在 Markdown 中引用转换后的.jpg文件。 - [关键] 输出内容的详略必须和论文叙述的详略一致。对于作者重点呈现的创新点详细阐述，对于论文中较简略的部分不花大篇输出。
- [关键] 自适应分析：严禁生搬硬套某一类论文的分析模板。
- [格式] 行文语言采用中文，各种术语直接保持用英文，是否简写与论文保持一致。不要中英混杂到难以阅读的程度。
- [格式] 对于文中出现的复杂数学定义，使用 Markdown 的 LaTeX 格式输出，并根据原文来解释表达式中的变量。严格区分两种公式格式：行内公式（inline）使用单 dollar 符号
$...$，嵌入在正文句子中；行间公式（display）使用双 dollar 符号$$...$$，必须独占一行且上下各留一个空行。禁止在行内公式中使用$$，禁止在行间公式中使用单$。变量、短表达式（如 $s_t$、$p>0$）用行内；独立推导、核心公式用行间。 - [格式] 保留有效的 Obsidian-style wikilinks
[[...]]；不要编造目标。 - [格式] 最终交付路径：只把讲义式笔记正文写到
{paper}/NOTES.md。 - [格式] 完成后标记已读：notes 和链接处理完后，始终运行
agentero paper set-read {paper} --json。 - [格式] Cite sources inline without wrapping parentheses. citation hrefs should target the local PDF
[Section 2.3](papers/<id>/<id>.pdf#section=2.3),[Figure 1](papers/<id>/<id>.pdf#figure=1),[p.11](papers/<id>/<id>.pdf#page=11), or notes[[papers/<id>/NOTES]]/[[papers/<id>/NOTES|short title]]. If a path segment contains a space, percent-encode it as%20(preferred) or wrap the destination in angle brackets. Do not leave a raw space outside<>.[p.4](papers/Quantum%20Error%20Correcting/<id>/<id>.pdf#page=4)[p.4](<papers/Quantum Error Correcting/<id>/<id>.pdf#page=4>)For web pages use[domain](https://...).
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 25d ago Changed · +4 lines 3444ca458470
- 1mo ago Changed · -105 lines · -9 tokens per session 541d8db43505
- 1mo ago Changed · +6 lines 8827334df388
- 1mo ago Changed · +2 lines 94eb51d50536
- 1mo ago First seen · 190 lines · 52 tokens per session scan A 44ae17511acc
paper-reader is a skill published in the GitHub repository poco-ai/Agentero (1,032 stars, last pushed today), licensed MIT. It adds 43 tokens to every session and 1,794 once invoked, about $0.0002 per session on Opus 5.5. 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.
Other skills, from other repositories
flashcards
Create strict JSON flashcard decks for active-recall study.
quiz
Create strict JSON single-answer multiple-choice quizzes.
edu-math-tutorial
A Chinese-language guide for turning a maths problem into a step-by-step teaching video. It explains how to break down the solution, write narration, format equations, and structure scenes.
clinical-q-and-a
A fast path for answering general educational medical questions and correcting common misconceptions, with a light check against one current authoritative guideline or consensus.
guideline-learning-diagnosis
A study aid for learning a medical guideline or its diagnostic criteria. It helps assess what someone knows, find weak sections, and plan further study without diagnosing a real patient.
paper-explainer
A research-content workflow that turns an arXiv paper or a local PDF into an explanation for a video or written article. arXiv is a public online archive of research papers.