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Analyseur de documents académiques Beautiful Soup

Extrait des données de citation structurées depuis des dépôts académiques à l'aide de BeautifulSoup4 avec l'analyseur lxml. Analyse les métadonnées DOI, les affiliations des auteurs et les listes de références à partir du HTML de PubMed, arXiv et Semantic Scholar.

Qu'est-ce que Analyseur de documents académiques Beautiful Soup ?

Cette compétence permet d'extraire des données de citation structurées à partir de dépôts académiques (PubMed, arXiv, Semantic Scholar) en utilisant BeautifulSoup4 avec l'analyseur lxml. Elle est conçue pour les développeurs et les chercheurs qui ont besoin de récupérer automatiquement des métadonnées DOI, des affiliations d'auteurs et des listes de références à partir de pages HTML. La compétence s'appuie sur la bibliothèque Python BeautifulSoup4, largement utilisée pour le scraping web et l'analyse de documents HTML. Avec cette compétence, un assistant IA peut lire des pages de dépôts académiques, localiser les éléments pertinents (balises de citation, liens DOI, listes de références) et les structurer en données exploitables. Elle est idéale pour automatiser la collecte de références bibliographiques, la recherche documentaire ou l'indexation de publications scientifiques. La compétence est compatible avec les environnements Python 3.7+ et utilise l'analyseur lxml pour une extraction robuste même à partir de HTML mal formé.

Compatible avec~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/agentskillexchange/skills/tree/main/skills/beautifulsoup-academic-paper-parser
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Documentation

Que fait Analyseur de documents académiques Beautiful Soup ?

Extrait des données de citation structurées depuis des dépôts académiques à l'aide de BeautifulSoup4 avec l'analyseur lxml. Analyse les métadonnées DOI, les affiliations des auteurs et les listes de références à partir du HTML de PubMed, arXiv et Semantic Scholar.

Installation

Utilisez la commande d'installation standard correspondant à votre environnement :

  • pip install beautifulsoup4
  • format. Lancez make html dans ce répertoire pour créer le HTML

Prérequis et remarques issues de la source officielle :

  • Nécessite : Python >=3.7.0
  • Python
  • Python :: 3

Notes d'utilisation de base ou pour débuter :

Source

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

Academic Paper Citation Network Mapper

Builds citation networks from Semantic Scholar API and CrossRef DOI metadata. Visualizes paper influence graphs using NetworkX, identifies seminal works, and tracks research lineage across fields.

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act Local GitHub Actions Runner

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Add a browser review checkpoint before risky agent actions with

Use AgentClick when an agent should pause before risky commands, plans, drafts, or code changes so a human can inspect, edit, approve, or reject them in a purpose-built browser UI.

Add Claude design-system and accessibility workflows with UX/UI

Use UX/UI Agent Skills when Claude should generate tokens, component specs, accessibility audits, and framework-specific UI code from a repeatable design workflow.

Add executable smoke tests for shell scripts and CLIs before ref

Use Bats-core when an agent needs to turn fragile shell scripts or command-line workflows into something it can verify repeatedly after edits. The agent writes focused Bash tests for success paths, failure paths, and output contracts, then runs them locally or in CI before a refactor, release, or incident fix goes out.

Add graph-backed memory and context retrieval to agent workflows

Use Cognee to ingest project knowledge into graph and vector memory so agents can retrieve durable context across sessions and workflows.

Add IDE-style semantic code navigation and symbol-safe refactors

Give a coding agent symbol-aware lookup, cross-file rename, and structural edit tools before it starts making brittle text-only changes.

Add managed long-term memory to LangGraph agents with LangMem

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Add multimodal lifelong memory to MCP and Python agents with Sim

Use SimpleMem to store, compress, index, and retrieve text or multimodal memories for agents through MCP or Python integrations.

Add persistent project memory and hook-driven synthesis with Cla

Keep Claude Code sessions grounded in prior decisions, project context, and daily handoff notes instead of starting from zero every time.

Add Postgres-native vector retrieval to agent and RAG workflows

Store embeddings beside application data in Postgres, create vector indexes, and query nearest neighbors for semantic search, RAG, recommendations, or agent memory retrieval.

Address GitHub PR review comments from the current branch with g

Find the open PR for the current branch, gather unresolved review comments, and drive a focused comment-resolution workflow with gh-authenticated context.

Add runtime guardrails to TypeScript agents with VoltAgent

Use VoltAgent to intercept, validate, and enforce input/output policies in TypeScript agent workflows.

Add temporal context memory to agent workflows with Zep

Use Zep as an external context layer for agents that need to store events, assemble temporal graph context, and retrieve relevant memory before model calls.

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Calls Adobe Firefly

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