Nature Literature Pipeline
SkillSearchnature-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.
Use Nature Literature Pipeline in Claude, ChatGPT or Ahel Desktop
Free. Sign in, add Nature Literature Pipeline and connect your AI. About a minute.
Also: Claude Code · Cursor · Codex
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.
Account requirements not reviewed. Check the skill instructions before use; ahel provides instructions and does not run this skill.
No other account needed.
Have an AI agent environment where skills can be installed.
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
- Have an AI agent environment where skills can be installed.
- Add the nature-literature-pipeline skill to the agent.
- Configure the search engine settings, including sources and scoring preferences.
- Set up a daily cron schedule for the application layer.
- 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:
| 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
- 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