nature-literature-pipeline

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:

Quick Start

After installing, tell your agent:

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

Then set up a daily cron job:

Architecture

The skill is organized in two layers:

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

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