Name: nature-literature-pipeline
Author: yuan1z0825

Imported from yuan1z0825/nature-skills (skills/nature-literature-pipeline/SKILL.md) via skills.sh. Install upstream with npx skills add yuan1z0825/nature-skills --skill nature-literature-pipeline. Copyright stays with the author (MIT).

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:

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

Install nature-literature-pipeline and it becomes one more candidate the router can pick - when it fits.

A listing is a routing target with a manifest: what it does, which domains it covers, what it costs and who publishes it. Once installed it sits beside your own models and tools, is scored like any other candidate for each request, and shows up in the trace when it wins. Ratings come from workspaces that installed it, one per account.

{ "ocm": "1", "id": "yuan1z0825-nature-skills-nature-literature-pipeline", "kind": "skill", "name": "nature-literature-pipeline", "description": "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.", "publisher": "yuan1z0825", "version": "1.0.0", "capabilities": { "domains": [ "customer_support" ], "tags": [ "skill-md", "skills-sh" ], "languages": [ "en" ] }, "quality_prior": 0.6, "examples": [ "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." ], "primary": false, "metadata": { "source": { "provider": "skills.sh", "repository": "https://github.com/yuan1z0825/nature-skills", "path": "skills/nature-literature-pipeline/SKILL.md", "ref": "HEAD", "url": "https://www.skills.sh/yuan1z0825/nature-skills/nature-literature-pipeline", "key": "yuan1z0825/nature-skills/skills/nature-literature-pipeline/SKILL.md" }, "license": "MIT" }, "instructions": "# Nature Literature Pipeline\n\nA 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.\n\n## What It Does\n\n```\nCron (daily trigger, e.g. 08:30)\n │\n ├─ ① SEARCH (30 candidates)\n │ arXiv / OpenAlex / Crossref / Semantic Scholar (auto-degradation)\n │\n ├─ ② COARSE FILTER (30 → 5)\n │ Six-dimension scoring: topic match × 35 + methodology × 20\n │ + journal quality × 15 + network relevance × 10\n │ + applied value × 10 + archival value × 10\n │\n ├─ ③ F", "cost": { "context_tokens": 1027 } }

nature-literature-pipeline

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