dailypaper-skills is a collection of agent skills that automates a research-paper reading workflow. It finds recent papers from sources such as Hugging Face and arXiv, ranks them by the user’s interests, and creates structured notes in Obsidian, with optional Zotero support. The catalogue skills are the project’s own workflow components for coding agents.
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 huangkiki/dailypaper-skills --skill daily-papersgit clone --depth 1 https://github.com/huangkiki/dailypaper-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/huangkiki/dailypaper-skills/daily-papers)<a href="https://agentmods.dev/skills/huangkiki/dailypaper-skills/daily-papers"><img src="https://agentmods.dev/badge/skills/huangkiki/dailypaper-skills/daily-papers/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/huangkiki/dailypaper-skills/daily-papers"><img src="https://agentmods.dev/badge/skills/huangkiki/dailypaper-skills/daily-papers.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 | $0.00073 | $0.00417 |
| Opus 5 | $0.00036 | $0.00209 |
| Sonnet 5 | $0.00015 | $0.00083 |
| Haiku 4.5 | $0.00007 | $0.00042 |
Grade A, and why
daily-papers 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 13d 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
每日论文推荐
这是面向用户的一句话入口。对用户来说，正常只需要说一次：
今日论文推荐过去3天论文推荐过去一周论文推荐
执行原则
- 先识别时间范围：
今日论文推荐、每日推荐、今日论文-> 当天过去3天论文推荐、最近3天论文-> 3 天过去一周论文推荐、看看这周有啥论文-> 7 天
- 自动调用
/daily-papers-fetch。 - 第 1 步完成后，自动调用
/daily-papers-review。 - 第 2 步完成后，自动调用
/daily-papers-notes。 - 全部完成后，用一句话告诉用户：
- 推荐文件已生成
- 重点论文笔记已生成多少篇
- 目录页是否已自动刷新
重要约束
- 不要先要求用户手动跑
跑一下论文抓取 / 点评 / 笔记。 - 这 3 句是内部流水线和调试入口，不是首页主交互。
- 如果用户明确只想跑其中一步，再交给对应 skill。
自动化
- 本 skill 本身就是“一步跑完整流水线”的入口。
- 如果用户想做本地定时任务，默认也应该触发这一句，而不是写死三条内部命令。
What ships with it
5 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.
- 13d ago First seen · 42 lines · 73 tokens per session scan A 060f12b763c1
daily-papers is a skill published in the GitHub repository huangkiki/dailypaper-skills (1,220 stars, last pushed 20d ago), licensed Apache-2.0. It adds 73 tokens to every session and 417 once invoked, about $0.0004 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.
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