Borrowing it
Nothing to install: this file belongs to dengls24/annota. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/dengls24/annota/master/.claude/skills/annota-read/SKILL.mdgit clone --depth 1 https://github.com/dengls24/annotaWrote 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/dengls24/annota/annota-read)<a href="https://agentmods.dev/skills/dengls24/annota/annota-read"><img src="https://agentmods.dev/badge/skills/dengls24/annota/annota-read/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/dengls24/annota/annota-read"><img src="https://agentmods.dev/badge/skills/dengls24/annota/annota-read.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00095 | $0.02098 |
| Opus 5 | $0.00048 | $0.01049 |
| Sonnet 5 | $0.00019 | $0.00420 |
| Haiku 4.5 | $0.00010 | $0.00210 |
Grade A, and why
annota-read scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 226 lines — stays where its author put it; the contents beside it link to each section on GitHub.
论文全套深度阅读
用户给了一篇论文,但没有具体指令。你的目标是给出开箱惊艳的阅读体验。
输入解析
用户输入:$ARGUMENTS
Step 1:快速扫描,生成论文概览
1.1 定位论文
如果是文件路径直接使用;否则调用 search_zotero_items(query) 搜索。
同时调用 get_item_metadata(item_id) 获取元数据。
1.2 提取全文
调用 get_pdf_text_bulk(item_id, skip_refs=True)。
1.3 输出论文快照(在对话中展示,不保存)
阅读全文后,用以下格式输出一段论文快照,让用户知道你已经读懂了:
📄 **{标题}**
👥 {作者} · {会议/期刊} {年份}
🎯 **一句话核心**:{用一句话说清楚这篇论文做了什么,解决了什么问题}
💡 **3个关键贡献**:
1. {贡献1}
2. {贡献2}
3. {贡献3}
📊 **最亮眼的数据**:{最重要的一两个实验结果数字}
⚠️ **主要局限**:{最关键的一个局限}
Step 2:交互式确认阅读方案
展示快照后,立即询问用户想要什么深度:
我已经读完了这篇论文。接下来你想要:
A) 🚀 **全套深度阅读**(推荐)
四色标注全文重点 + 结构化阅读笔记保存到 Zotero
预计创建 15-25 条标注 + 1 份完整笔记
B) 🎨 **只做标注**
四色高亮:贡献(紫)、方法(蓝)、结果(绿)、不足(红)
预计 15-25 条标注
C) 📝 **只写笔记**
生成结构化阅读笔记保存到 Zotero
D) 🔍 **审稿模式**
以顶会审稿人视角给出评审意见 + 评分
E) 🎯 **自定义**
告诉我你最关心什么(某个具体方法、某类实验、某个问题)
直接回复 A/B/C/D/E,或者告诉我你想要什么。
Step 3A:全套深度阅读(选 A)
标注阶段
分析全文,识别以下四类内容,每类至少找 3-5 处:
| 类型 | 颜色 | 代码 | 标准 |
|---|---|---|---|
| 核心贡献/创新点 | 紫色 | #a28ae5 | 论文声称的 novelty、contribution |
| 方法/架构/算法 | 蓝色 | #2EA8E5 | 关键技术设计、核心机制 |
| 实验结果/数据 | 绿色 | #28CA42 | 具体数字、性能对比、improvement |
| 局限/不足/future work | 红色 | #ff6666 | limitation、weakness、future work |
输出标注清单(在对话中展示):
将创建以下标注:
[紫] Page 1: "We propose DCC, a novel..."
[蓝] Page 3: "The key insight is..."
[绿] Page 6: "achieves 2.3× speedup over..."
...(共 N 条)
⚠️ 写入需要关闭 Zotero。请确认已关闭后回复"确认"。
用户确认后,调用 batch_annotate 一次性写入所有标注。
笔记阶段
生成完整结构化笔记(HTML 格式),内容比 /annota-summarize 更深入:
<h2>📄 论文信息</h2>
<p><b>标题:</b>{title}</p>
<p><b>作者:</b>{authors}</p>
<p><b>发表:</b>{venue} {year}</p>
<p><b>DOI:</b>{doi}</p>
<h2>🎯 核心问题与动机</h2>
<p><b>问题:</b>{这篇论文要解决什么问题?}</p>
<p><b>为什么重要:</b>{这个问题的重要性和现有方案的不足}</p>
<h2>💡 核心贡献(对应紫色标注)</h2>
<ol>
<li><b>{贡献1标题}:</b>{具体说明}</li>
<li><b>{贡献2标题}:</b>{具体说明}</li>
<li><b>{贡献3标题}:</b>{具体说明}</li>
</ol>
<h2>🔧 方法详解(对应蓝色标注)</h2>
<p><b>整体架构:</b>{一段话描述整体方案}</p>
<p><b>关键设计1:</b>{设计决策及其原因}</p>
<p><b>关键设计2:</b>{设计决策及其原因}</p>
<h2>📊 实验结果(对应绿色标注)</h2>
<ul>
<li><b>主要结论:</b>{最重要的实验结论}</li>
<li><b>关键数据:</b>{具体数字,如"比 baseline 快 2.3×"}</li>
<li><b>Baseline 对比:</b>{与哪些方法对比,结果如何}</li>
</ul>
<h2>⚠️ 局限与不足(对应红色标注)</h2>
<ul>
<li><b>论文自述:</b>{作者承认的 limitation}</li>
<li><b>潜在问题:</b>{你认为的其他不足}</li>
</ul>
<h2>💭 批判性思考</h2>
<p><b>最强的地方:</b>{这篇论文最有说服力的点}</p>
<p><b>最弱的地方:</b>{最值得质疑的地方}</p>
<p><b>可复现性:</b>{实验设置是否清晰,能否复现}</p>
<h2>🔗 对我的启发</h2>
<p>{这篇论文对读者自己研究的启发,如果知道用户研究方向则定制}</p>
<h2>📚 值得追读</h2>
<ul>
<li>{引用中最值得读的 2-3 篇相关工作}</li>
</ul>
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.
- 10d ago First seen · 226 lines · 95 tokens per session scan A 4b6632cb6584
annota-read is a skill published in the GitHub repository dengls24/annota (19 stars, last pushed 4mo ago), licensed MIT. It adds 95 tokens to every session and 2,098 once invoked, about $0.0005 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.
Other skills, from other repositories
fs-notebook-tabs
A computer-science capstone: an on-device ML keyboard that predicts next words privately — problem, method, evaluation, and defense answers. Built as a decision-grade coursework defense deck for professor, defense committee.
html-ppt-zhangzara-cartesian
An economics senior thesis on the employment effects of local minimum-wage increases — identification strategy, evidence, and limitations. Built as a decision-grade coursework defense deck for thesis committee.
html-ppt-zhangzara-pin-and-paper
A field-biology capstone on urban pollinator decline — the survey design, the data, the contribution, and the caveats. Built as a decision-grade coursework defense deck for faculty reviewers.
html-ppt-zhangzara-scatterbrain
A design-school graduation project: a civic wayfinding system for a transit hub — the brief, the process, and the outcome. Built as a decision-grade coursework defense deck for crit panel, faculty.
Academic CV Builder
Format CVs for academic positions with publications, grants, and teaching.
paper-slide-deck
Generate professional slide deck images from academic papers and content. Creates comprehensive outlines with style instructions, auto-detects figures from PDFs, then generates individual slide images. Use when user asks to "create slides", "make a presentation", "generate deck", or "slide deck" for papers.