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 github-trendinggit 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/github-trending)<a href="https://agentmods.dev/skills/huangkiki/dailypaper-skills/github-trending"><img src="https://agentmods.dev/badge/skills/huangkiki/dailypaper-skills/github-trending/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/github-trending"><img src="https://agentmods.dev/badge/skills/huangkiki/dailypaper-skills/github-trending.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 | $0.00141 | $0.01445 |
| Opus 5.5 | $0.00056 | $0.00578 |
| Sonnet 5.5 | $0.00028 | $0.00289 |
| Haiku 4.5 | $0.00014 | $0.00145 |
Grade A, and why
github-trending 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 16d 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 — 103 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Language / 语言
First resolve OUTPUT_LANGUAGE using language selection.
For an English request (or an explicit request for English), read and follow
the English workflow instead of the Chinese body below.
中文请求继续执行下文；用户明确指定的语言优先。内部阶段继承语言，不从论文或工具输出重新判断。
执行环境
开始前读取 Agent 运行约定，解析当前 Skill 目录、有效配置和 TEMP_DIR，再执行下文。
开始前: 先说一声 "开始抓 GitHub 榜单 🐙" 并告知今天日期与抓取周期（默认周榜）。
GitHub Trending 抓取
抓取 GitHub Trending + 按主题搜索仿真新项目 / 近期更新 → 标注研究相关性 → 写成 Obsidian 笔记。纯 Python 脚本，脚本本身不调用大模型。
Step 0: 读取共享配置
运行 python3 ../_shared/user_config.py 读取有效配置及 runtime.temp_dir。
脚本内部已通过 ../_shared/user_config.py 自动加载，无需手动传参。相关字段：
paths.obsidian_vault— vault 根路径paths.github_trending_folder— 输出文件夹（默认GitHubTrending）daily_papers.keywords / negative_keywords / domain_boost_keywords— 复用它们给项目打分、标注相关性daily_papers.project_queries— 广泛检索仿真引擎、求解器与相关基础设施；项目名示例不构成白名单
解析周期与语言
从用户输入解析 --since：
- "周榜"、"过去一周"、"这周"、"本周" →
--since weekly（默认） - "日榜"、"今天"、"今日" →
--since daily - "月榜"、"这个月"、"本月" →
--since monthly
可选 --language（如 "只看 Python" → --language python），不指定则抓全部语言。
工作流程
Phase 1: 抓取 + 打分（fetch_trending.py）
python3 fetch_trending.py --since weekly --output "{TEMP_DIR}/github_trending.json"
# 指定语言示例：
# python3 fetch_trending.py --since weekly --language python --output "{TEMP_DIR}/github_trending.json"
脚本自动完成：
- 抓取
github.com/trending?since=<周期>（兼容 SSL 拦截环境，自动退回不验证证书） - regex 解析：repo、简介、语言、累计 star/fork、本周期新增 star
- 用共享配置关键词打分，标注
relevant（命中正向/领域词且未被负向词压过），不丢弃非相关项 - 按本周期新增 star 降序排序
检查输出：确认 {TEMP_DIR}/github_trending.json 是非空 JSON 数组。为空则看 stderr 诊断。
Phase 1b: 发现新项目和生态更新
python3 discover_projects.py --days 7 --output "{TEMP_DIR}/github_projects.json"
按用户周期选择天数（日榜 1、周榜 7、月榜 30）。该步骤使用 GitHub Repository Search，在研究主题范围中分别查询 created 与 pushed 日期，补足 Trending 未收录的新项目。每个查询最多 10 个项目，不保证穷尽。可从环境读取 GITHUB_TOKEN / GH_TOKEN；不输出或保存密钥。
What ships with it
4 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.
- 16d ago Changed · +9 lines · +32 tokens per session 011c0c3e0eb6
- 23d ago Changed · +18 lines 7778d5834753
- 1mo ago First seen · 76 lines · 109 tokens per session scan A 7db3ffcbf2fb
github-trending is a skill published in the GitHub repository huangkiki/dailypaper-skills (1,320 stars, last pushed today), licensed Apache-2.0. It adds 141 tokens to every session and 1,445 once invoked, about $0.0006 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.
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