Nature Literature Pipeline
SkillSearchLets 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.
No other account needed.
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:
| 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
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
| Reference | Purpose |
|---|---|
references/scoring-system.md | Six-dimension scoring rubric with weights, caps, and evaluation logic |
references/gap-analysis.md | Methodology for identifying research gaps through systematic literature survey |
references/note-template.md | Standardized literature note format with YAML frontmatter |
references/push-format.md | Daily digest message template with field guidelines and example |
references/cron-setup.md | Cron job creation, verification, and manual fallback procedures |
references/review-compilation-workflow.md | End-to-end workflow for concentrated literature review writing |
Pitfalls
- Keyword drift: Review keywords monthly — research directions evolve
- Score inflation: Subagents may inflate scores; always validate arithmetic
- Duplicate creep: Classic papers will reappear; maintain a dedup index
- Wiki safety: Pipeline writes to
raw/only; wiki integration is manual - Cron locality: Hermes cron is local, not cloud — machine must be running
Signals
- GitHub stars
- 41k
- Forks
- 2k
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
nature-literature-pipeline- Source
- github.com/yuan1z0825/nature-skills