nature-literature-pipeline
Automate Your Research Literature Pipeline
Keeping current with research requires repeated searching, filtering, reading, and organizing. This skill defines a configurable workflow for recurring discovery, delivery, and archival.
Установить с помощью моего Агента
Скопируйте этот запрос в своего Агента. Он содержит каноническую страницу Skill и манифест.
Review the Skillstore skill "nature-literature-pipeline" from https://skillstore.io/skills/yuan1z0825-nature-literature-pipeline.md and its manifest at https://skillstore.io/api/skills/yuan1z0825-nature-literature-pipeline/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.Ваш Агент по-прежнему должен показать план и запросить все подтверждения, требуемые политикой безопасности.
Ресурсы для AI-агентов
Используйте эти ссылки, когда AI-агенту, crawler или script нужен чистый контекст вместо полной страницы.
Протестировать
Использование «nature-literature-pipeline». Track machine learning methods for marine concrete durability during the last seven days.
Ожидаемый результат:
A ranked digest lists five deduplicated papers with scores, reading depth, methods, specific results, limitations, and stable source links.
Использование «nature-literature-pipeline». Check whether a four-component material system has been studied and document the search.
Ожидаемый результат:
- A concise conclusion distinguishes a confirmed gap from partial overlap.
- A subsystem table classifies direct, adjacent, and unrelated evidence.
- A reproducibility section records search terms, sources, hit counts, and follow-up work.
Использование «nature-literature-pipeline». Prepare a reusable daily literature push for a research group.
Ожидаемый результат:
A configurable profile defines topics, exclusions, source priority, scoring weights, delivery target, archive settings, and a verification checklist.
Аудит безопасности
БезопасноAll 28 static detections are false positives caused by Markdown formatting, benign examples, ordinary prose, or UTF-8 Chinese text. No prompt injection, malicious execution instructions, credential exposure, or covert data transfer was found in the reviewed files.
Факторы риска
🌐 Доступ к сети (1)
⚙️ Внешние команды (20)
Поделиться и цитировать этот отчет
Делитесь версионным отчетом об оценке, нейтральным значком, встраиваемой карточкой и цитатами. Skillstore публикует доказательства, не решая, безопасен ли этот Skill.
Копировать ссылку на отчёт
https://skillstore.io/skills/yuan1z0825-nature-literature-pipeline/audits/2?utm_source=security_passport&utm_medium=share&utm_campaign=versioned_reportЗначок Markdown
[](https://skillstore.io/skills/yuan1z0825-nature-literature-pipeline?utm_source=security_passport_badge)Значок HTML
<a href="https://skillstore.io/skills/yuan1z0825-nature-literature-pipeline?utm_source=security_passport_badge"><img src="https://skillstore.io/badges/skills/yuan1z0825-nature-literature-pipeline/security.svg" alt="Skillstore security assessment" loading="lazy"></a>Встраиваемая карточка
<iframe src="https://skillstore.io/embed/skills/yuan1z0825-nature-literature-pipeline.html" title="Skillstore Security Assessment" sandbox="allow-popups allow-popups-to-escape-sandbox" loading="lazy" referrerpolicy="no-referrer" width="420" height="180"></iframe>Академические ссылки (APA · BibTeX · CFF)
Цитата APA
yuan1z0825. (2026). nature-literature-pipeline security audit report (audit version 2) [Author version unspecified]. Skillstore. https://skillstore.io/skills/yuan1z0825-nature-literature-pipeline/audits/2Цитата BibTeX
@techreport{yuan1z0825-yuan1z0825-nature-literature-pipeline-2026,
author = {yuan1z0825},
title = {nature-literature-pipeline security audit report (audit version 2)},
institution = {Skillstore},
year = {2026},
number = {2},
url = {https://skillstore.io/skills/yuan1z0825-nature-literature-pipeline/audits/2},
note = {Author version unspecified}
}CITATION.cff
cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "nature-literature-pipeline security audit report (audit version 2)"
version: "unspecified"
type: report
authors:
- name: "yuan1z0825"
date-released: "2026-08-18"
url: "https://skillstore.io/skills/yuan1z0825-nature-literature-pipeline/audits/2"
identifiers:
- type: other
value: "skillstore:yuan1z0825-nature-literature-pipeline:audit:2"
description: "Skillstore immutable audit report identifier"
Оценка Skillstore
Почему такая оценка Достоверность доказательств: СреднийЧто вы можете построить
Monitor a Research Topic
Create a daily or weekly digest of new papers for a defined topic, keyword set, and exclusion list.
Build a Team Reading Queue
Rank recent candidates and deliver focused summaries that help a research group select papers for deeper reading.
Map a Literature Gap
Search related systems, classify direct and adjacent evidence, and prepare a reproducible gap report for a new project.
Попробуйте эти промпты
Create a weekly literature pipeline for [topic]. Search [sources], review the last [days] days, and return the top [count] papers.
Monitor [topic] using these keywords: [keywords]. Exclude [terms]. Score [candidate count] papers and deliver the top [final count] to [target].
Build a recurring pipeline for [topic]. Deduplicate by stable identifiers, label reading depth, archive raw notes under [path], and verify delivery separately.
Investigate whether [research question] is a documented gap. Search exact and adjacent terms across three sources. Record queries, evidence tiers, limitations, and next steps.
Лучшие практики
- Review keywords and score distributions after several runs, then adjust weights with the user.
- Label every paper as full text, abstract only, metadata only, or project page reviewed.
- Verify scheduling, delivery, archival, deduplication, and failure alerts as separate stages.
Избегать
- Do not treat a high score as proof of paper quality or relevance.
- Do not claim full-text findings when only metadata or an abstract was available.
- Do not place private chat identifiers, API keys, or machine-specific paths in shared templates.
Часто задаваемые вопросы
Which literature sources does this skill support?
Does the skill create scheduled jobs by itself?
Can it send digests to messaging platforms?
How does it prevent duplicate papers?
What happens when full text is unavailable?
Does the scoring system replace expert judgment?
Сведения для разработчиков
Автор
yuan1z0825Лицензия
MIT
Ревизия Skillstore
r1
Примечание о версии
Автор не указал версию.
Ссылка
e22f0e5c175a84e01097fa734ec2a74420c14771
Актуальность поддержки
19.08.2026
Использование
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