Nature Literature Pipeline

SkillSearch

Lets your agent search academic papers across sources, score them, and deliver formatted summaries to your chat app.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Nature Literature Pipeline skill

About this capability

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.

What this skill tells your AI

The instructions your AI receives, as published by yuan1z0825/nature-skills in skills/nature-literature-pipeline/SKILL.md and read by ahel’s review.

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

Signals

GitHub stars
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Forks
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Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
nature-literature-pipeline
Source
github.com/yuan1z0825/nature-skills