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 chtc66/academic-skills --skill paper-deep-notegit clone --depth 1 https://github.com/chtc66/academic-skillsWrote 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/chtc66/academic-skills/paper-deep-note)<a href="https://agentmods.dev/skills/chtc66/academic-skills/paper-deep-note"><img src="https://agentmods.dev/badge/skills/chtc66/academic-skills/paper-deep-note/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/chtc66/academic-skills/paper-deep-note"><img src="https://agentmods.dev/badge/skills/chtc66/academic-skills/paper-deep-note.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 | $0.00054 | $0.00576 |
| Opus 5.5 | $0.00022 | $0.00230 |
| Sonnet 5.5 | $0.00011 | $0.00115 |
| Haiku 4.5 | $0.00005 | $0.00058 |
Grade A, and why
paper-deep-note 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 1mo 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
Paper Deep Note
用这个 skill 处理单篇论文精读。优先输出中文精读卡，强调研究问题、方法、证据、局限和对当前研究的启发。
工作流
- 先判断输入证据级别：全文、局部正文、摘要、仅标题。
- 明确声明判断边界。
- 按
references/note_template.md输出结构化精读卡。 - 在需要判断是否值得继续读时，参考
references/reading_guidelines.md。
输入处理规则
- 接收 PDF、arXiv 链接、标题加摘要、正文片段或用户自述笔记。
- 如果只有摘要或标题，明确写出“仅基于摘要判断”或“仅基于标题与摘要判断”。
- 如果实验设置、数据集、指标或结果未在输入中明确给出，直接标记为未知，不要补全想象内容。
- 如果用户给出的是局部正文，区分“原文明确给出”和“由局部内容推测”。
输出规则
- 默认输出完整精读卡。
- 如果用户只想快速筛论文，保留相同字段，但压缩每项长度。
- 在“优势”“局限”“复现难点”“启发”部分，优先给出和 AI / NLP / LLM / Agent / RAG / Safety 研究直接相关的判断。
- 在“是否值得精读”部分，只使用以下标签之一：
值得精读值得速读可暂缓
证据与表述约束
- 不要假装读过未提供的全文。
- 不要把论文 claim 直接改写成既定事实。
- 不要编造实验结果、消融结论、数据集细节或开源状态。
- 如果判断主要基于摘要，弱化关于方法细节和实验设计的断言。
何时读引用文件
- 始终读取
references/note_template.md以保持输出结构稳定。 - 在判断阅读优先级、复现难点或阅读深度时，读取
references/reading_guidelines.md。
默认交付
- 默认给出长版中文精读卡。
- 如果信息不足，在卡片顶部先给出“输入覆盖范围说明”。
What ships with it
3 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.
- 1mo ago First seen · 50 lines · 54 tokens per session scan A d03d9c2884b1
paper-deep-note is a skill published in the GitHub repository chtc66/academic-skills (366 stars, last pushed 6mo ago), licensed MIT. It adds 54 tokens to every session and 576 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
hr-onboarding
A new-hire onboarding plan as a single page — first week schedule, buddy + manager intro, learning track, equipment checklist, and "you're set when…" outcomes. Use when the brief mentions "onboarding", "new hire", "first week plan", or "入职".
book-mirror
Take any book (EPUB/PDF), produce a personalized chapter-by-chapter analysis. Each chapter is preserved in detail (The Chapter) and mirrored back to the reader's actual life (The Mirror) using brain context. The mirror observes and resonates — a friend pointing out parallels, NOT a consultant rearranging the reader's…
exam-forecast
Analyze past exams from the same professor to surface patterns — subject weighting, recurring issue-spot traps, favored hypo types, policy-vs-doctrine mix — and forecast likely emphases for the upcoming exam. Use when the user says "what's on the exam", "analyze past exams", "predict the exam", or shares past exams.
lean-formalize
Develop and verify a mathematical proof in Lean, continue an incomplete Lean project, or audit whether it proves the original statement. Connect actual inputs to intermediate lemmas, assemble the target theorem, check its transitive axioms, and provide a reproducible handoff. Use when Lean is requested or a specific…
eli5
Explain research, papers, or technical ideas in plain English with minimal jargon, concrete analogies, and clear takeaways. Use when the user says "ELI5 this", asks for a simple explanation of a paper or research result, wants jargon removed, or asks what something technically dense actually means.
deck-course-module
A course or workshop slide template with persistent learning goals, teaching pages, multiple-choice self-tests, and a wrap-up.