nature-literature-pipeline

nature-literature-pipeline is a skill for Codex from Yuan1z0825/nature-skills. It costs 53 tokens per session (1,126 once invoked), scanned A, original, Apache-2.0.

An automated daily workflow for finding research papers, ranking them, reading the best matches, sending a summary, and keeping an archive. It searches sources such as arXiv, a preprint site, and OpenAlex, a research-index database.

In plain words
What is it for?
Use it to monitor a research topic each day, receive ranked paper digests in Feishu, Telegram, or another messaging service, and maintain indexed notes and an archive.
Why use it?
It reduces the time spent searching many paper databases and deciding what deserves attention. It also helps prevent duplicate records and scattered notes.

Skill for Codex

Written for Codex: agents/openai.yaml present. Also seen: mentions subagents.

Good fit Use it to monitor a research topic each day, receive ranked paper digests in Feishu, Telegram, or another messaging service, and maintain indexed notes and an archive.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/yuan1z0825/nature-skills/nature-literature-pipeline
About the project

Nature Skills is a collection of reusable skills that help AI agents handle academic writing and scientific visualization. Researchers and AI-assisted scholars use it to turn research tasks into repeatable workflows and usable outputs. The catalogue entries are skills from this collection.

Yuan1z0825/nature-skills · 50,803 stars · on GitHub

Install

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.

Any agent
npx skills add Yuan1z0825/nature-skills --skill nature-literature-pipeline
Clone the repo
git clone --depth 1 https://github.com/Yuan1z0825/nature-skills

Made for: Codex.

Wrote 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.

agentmods badge for nature-literature-pipeline

README.md
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Your own site
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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.

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Your own site · 80×15
<a href="https://agentmods.dev/skills/yuan1z0825/nature-skills/nature-literature-pipeline"><img src="https://agentmods.dev/badge/skills/yuan1z0825/nature-skills/nature-literature-pipeline.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 53 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,126 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. ✓ AI security review Sonnet 5 · 6 Sept 2026 📄 Read the review Third-party audits
  • Socket pass 4 Aug 2026
  • Snyk warn 4 Aug 2026
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00053 $0.01126
Opus 5.5 $0.00021 $0.00450
Sonnet 5.5 $0.00011 $0.00225
Haiku 4.5 $0.00005 $0.00113

Measured 1mo ago against content hash 1dcaa692457e, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

nature-literature-pipeline 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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

skills/nature-literature-pipeline/SKILL.md · 113 lines

How it starts

The opening of the file, as written. The whole thing — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Nature Literature Pipeline

A complete, production-tested automated literature pipeline. Not just "search for papers" — it's a structured engine that scores, classifies, reads, delivers, and archives research papers daily.

What It Does

Cron (daily trigger, e.g. 08:30)
  │
  ├─ ① SEARCH (30 candidates)
  │   arXiv / OpenAlex / Crossref / Semantic Scholar (auto-degradation)
  │
  ├─ ② COARSE FILTER (30 → 5)
  │   Six-dimension scoring: topic match × 35 + methodology × 20
  │   + journal quality × 15 + network relevance × 10
  │   + applied value × 10 + archival value × 10
  │
  ├─ ③ FINE READ (top 5)
  │   Abstract-level or full-text. Source level tagged:
  │   Full-text / Abstract only / Metadata only
  │
  ├─ ④ DELIVER
  │   Formatted digest to Feishu/Telegram/etc.
  │   🏅 rank | title | journal | ⭐ score | 💡 one-liner
  │   🔬 methods | 📊 key results | 🧭 commentary
  │
  └─ ⑤ ARCHIVE
      DOI/arXiv de-dup → classify → write notes → update index

Quick Start

After installing, tell your agent:

My research area is [X], keywords: [Y], deliver to [feishu group name], archive to [path]

The agent will configure keywords, delivery target, and archive path automatically.

Then set up a daily cron job:

Set up a daily literature push at 08:30 Beijing time, 30 candidates, top 5 delivered

Architecture

The skill is organized in two layers:

Layer Purpose Files
Engine Scoring, classification, note templates, gap analysis references/scoring-system.md, references/gap-analysis.md, references/note-template.md
Application Daily cron pipeline, delivery formatting, archival workflow references/push-format.md, references/cron-setup.md, references/review-compilation-workflow.md

Configuration

All domain-specific content is configurable:

  • Keywords — your research keywords (English + Chinese)
  • Scoring weights — adjust the six dimensions for your field
  • Classification rules — define your own tier system (A-E or custom)
  • Delivery target — Feishu group, Telegram channel, email, etc.
  • Archive path — local vault/wiki directory

Read the full file on GitHub · 113 lines

Changes

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.

  1. 1mo ago First seen · 113 lines · 53 tokens per session scan A 1dcaa692457e

Subscribe to this mod's changes

nature-literature-pipeline is a skill published in the GitHub repository Yuan1z0825/nature-skills (50,803 stars, last pushed 2d ago), licensed Apache-2.0. It adds 53 tokens to every session and 1,126 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.

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