yuan1z0825/nature-skills

nature-literature-pipeline

Complete automated literature discovery pipeline: multi-source search → six-dimension scoring → fine reading → formatted delivery → archival.

Quelltext ansehen

Verwendung

  1. Installationsbefehl kopieren und das Quellpaket vor der Installation in der eigenen Agentenumgebung prüfen.
  2. Benötigte Werkzeuge, Zugangsdaten und Hosts im Original prüfen.
  3. Eingabe und gewünschtes Ergebnis beschreiben und die Ausgabe mit den Quellen abgleichen.
npx skills add https://github.com/yuan1z0825/nature-skills --skill nature-literature-pipeline

Vor dem Start

  • Die Installation umfasst weder Modellabo noch API-Kontingent oder Dateizugriffsrechte.
  • Sterne und Installationen zeigen Aktivität, keine unabhängige Qualitäts- oder Sicherheitsprüfung.
Originales Skill-Dokument

Aus dem Quell-Repository gerendert; Überschriften, Beispiele, Code, Tabellen, Links und Bilder bleiben erhalten.

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:
  │   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

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