Nature Literature Pipeline

SkillSearch

nature-literature-pipeline is a skill that gives an AI agent an automated literature discovery pipeline. It searches academic literature across multiple sources, scores results along six dimensions, reads the most relevant papers in depth, and delivers formatted digests to a chat platform such as Feishu or Telegram. A configurable engine handles the search and scoring, while a cron-driven application layer runs it daily and archives what it finds.

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Then ask your AI: use the Nature Literature Pipeline skill

Details

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

Have an AI agent environment where skills can be installed.

Nature Literature PipelineStart free

What your AI can do with it

  • Search academic literature across multiple sources
  • Score search results along six dimensions
  • Perform fine reading of selected papers
  • Deliver formatted digests to Feishu, Telegram, or other messaging platforms
  • Run the pipeline automatically on a daily cron schedule
  • Archive discovered literature for later reference

Getting started

  1. Have an AI agent environment where skills can be installed.
  2. Add the nature-literature-pipeline skill to the agent.
  3. Configure the search engine settings, including sources and scoring preferences.
  4. Set up a daily cron schedule for the application layer.
  5. Connect a delivery channel such as Feishu or Telegram to receive formatted digests.

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
45k
Forks
2k
Last commit
Sep 2026

Questions

Which messaging platforms does it work with?
It works with Feishu, Telegram, or any messaging platform.
How does it decide which papers matter?
Search results are scored along six dimensions, and the pipeline then performs fine reading on the papers that rank highest.
Does it run automatically?
Yes. A cron-driven application layer runs the pipeline daily, and the engine itself is configurable.
What happens to the papers it finds?
The pipeline archives the literature it discovers as part of its final step.
Advanced
Item type
skill
Key
nature-literature-pipeline
Source
github.com/yuan1z0825/nature-skills