Nature Literature Pipeline

by yuan1z0825d5c8baa15d6bMIT46K starsListed Oct 8, 2026Updated Oct 8, 2026Repository updated today

Complete automated literature discovery pipeline: multi-source search → six-dimension scoring → fine reading → formatted delivery → archival. Combines a configurable engine with daily cron-driven application layer. Works with Feishu, Telegram, or any messaging platform.

AI-generated overview

Automated daily literature discovery pipeline that searches, scores, reads, delivers and archives research papers.

What it does
This skill defines a structured, cron-driven literature pipeline: it searches arXiv, OpenAlex, Crossref and Semantic Scholar for candidate papers, applies a six-dimension weighted scoring rubric to filter them, fine-reads the top items, and formats a digest for delivery to a messaging platform such as Feishu or Telegram. It then de-duplicates by DOI or arXiv ID, classifies results and writes standardized literature notes into an archive directory. It is instruction-only, with reference documents covering scoring, gap analysis, note templates, push formatting, cron setup and review compilation.
When to use it
Use it when you want recurring, automated literature monitoring for a defined research area rather than one-off searches. It suits researchers who need daily ranked digests of new papers plus a growing, de-duplicated note archive. It also fits concentrated literature review compilation work.
Requirements
No scripts ship with the skill; it is instructions and reference documents only. It requires an agent able to run scheduled cron jobs on a machine that stays running, network access to the literature APIs (arXiv, OpenAlex, Crossref, Semantic Scholar), and a delivery target such as a Feishu group or Telegram channel. Keywords, scoring weights, classification rules, delivery target and archive path must be configured.

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:

LayerPurposeFiles
EngineScoring, classification, note templates, gap analysisreferences/scoring-system.md, references/gap-analysis.md, references/note-template.md
ApplicationDaily cron pipeline, delivery formatting, archival workflowreferences/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

A config template is provided in templates/literature-push-template.md.

Built-in Safeguards

  • Score validation: Each dimension capped, total recalculated — no 11/10 allowed
  • Triple de-duplication: DOI / arXiv ID / OpenAlex ID
  • Graceful degradation: Semantic Scholar down → auto-switch to OpenAlex + Crossref + arXiv
  • Read-only archive: Daily pipeline writes to raw/ literature directory only; never modifies wiki/knowledge base without user approval

Related Skills

  • nature-academic-search — ad-hoc literature search (complementary; this skill adds structured daily automation)
  • nature-citation — CNS citation export (for importing pipeline discoveries into manuscripts)
  • zotero — library management (for long-term organization of pipeline outputs)
  • arxiv — arXiv API (used as a search source)

References

ReferencePurpose
references/scoring-system.mdSix-dimension scoring rubric with weights, caps, and evaluation logic
references/gap-analysis.mdMethodology for identifying research gaps through systematic literature survey
references/note-template.mdStandardized literature note format with YAML frontmatter
references/push-format.mdDaily digest message template with field guidelines and example
references/cron-setup.mdCron job creation, verification, and manual fallback procedures
references/review-compilation-workflow.mdEnd-to-end workflow for concentrated literature review writing

Pitfalls

  1. Keyword drift: Review keywords monthly — research directions evolve
  2. Score inflation: Subagents may inflate scores; always validate arithmetic
  3. Duplicate creep: Classic papers will reappear; maintain a dedup index
  4. Wiki safety: Pipeline writes to raw/ only; wiki integration is manual
  5. Cron locality: Hermes cron is local, not cloud — machine must be running

Source and attribution

Source:yuan1z0825/nature-skillsinskills/nature-literature-pipelineat commitd5c8baa

License: MIT

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