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nature-literature-pipeline

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.

DeepseekModel Curated skill Quality Excellent · 90 v1.0.0

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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. license MIT metadata {"author":"Jiahao8595","hermes":{"tags":["research","literature","pipeline","cron","automation","discovery"],"related_skills":["nature-academic-search","nature-citation","arxiv","zotero"]}} 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
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Field Description
formatFormat tag (skill/v1)
skill_idUnique skill ID
nameSkill name
versionVersion
descriptionDescription
categoryCategories (array)
trigger_wordsTrigger words
tagsTags
sourceSource
source_urlSource URL (this page)
exported_atExported at (set per download)
system_promptSystem prompt body
model_configModel config: provider / model / temperature / max_tokens / top_p
examplesExamples
install_guideImport guide for Coze / Dify / Claude / custom frameworks
The same skill can be exported in different platform formats.
.skill Standard format with system_prompt and model_config, ready for any agent framework Download
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Coze Markdown with frontmatter, for Coze platform import Download
Dify Dify DSL, import directly after creating an app Download

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