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Scientific Research And Analysis Skills

claude-scientific-skills

sickn33/antigravity-awesome-skills

This skill provides comprehensive guidance and established patterns for conducting rigorous scientific research and complex data analysis. It helps users structure their thinking process, ensuring a systematic and methodical approach to scholarly inquiry. Ideal for academic projects, literature reviews, and complex data interpretation.

Materials Structure Toolkit

K-Dense-AI/claude-scientific-skills

A Python materials science library for constructing, analyzing, and converting crystal structures, computing phase diagrams and electronic properties, and integrating with the Materials Project API for high-throughput workflows.

Manage Annotation Configs and Queues

arize-annotation

github/awesome-copilot

This skill provides comprehensive management for annotation schemas (configs) and human review workflows (queues) within the Arize platform. It supports defining categorical, continuous, and freeform label types. Users can programmatically apply these annotations to project spans and datasets using the Python SDK, facilitating structured human feedback loops and improving model monitoring.

Manage Research Projects and Papers

K-Dense-AI/scientific-agent-skills

The Paperzilla skill provides direct command-line access to interact with Paperzilla data. Users can fetch the latest research recommendations, summarize canonical papers in markdown format, view project feeds, leave feedback, and export data in various formats (JSON, Atom). It is essential for researchers needing structured insights into academic projects and literature.

Pymatgen Materials Analysis

K-Dense-AI/scientific-agent-skills

Analyze, validate, convert, and transform materials structures and computed data using pymatgen APIs, including symmetry, phase diagrams, and bounded Materials Project queries with provenance.

Bright Data Web Scraping & SERP API

brightdata-core-workflow-b

jeremylongshore/claude-code-plugins-plus-skills

This skill provides comprehensive access to Bright Data's SERP API and Web Scraper API. It allows users to collect structured search engine results (Google, Bing, Yahoo) synchronously, or trigger large-scale, asynchronous data collections with webhooks. Ideal for market research, SEO analysis, and large-scale data scraping projects.

Claude Memory Bridge for Unified Search

This memory bridge ingests Claude Code's local auto-memory markdown files and structures them into AgentDB. It generates high-fidelity ONNX embeddings, handles deduplication using cosine similarity, and indexes the memories in a scalable namespace. This enables seamless, unified semantic search across all historical sessions and projects, significantly enhancing RAG capabilities.

Guiding Research Topic Selection for Sensor Systems

ipsn-topic-selection

brycewang-stanford/Awesome-Journal-Skills

This guide helps researchers determine the primary focus of their work—whether it lies in Information Processing (algorithms, estimation) or Sensor Platforms, Tools, and Design Methods (hardware, deployment). It provides a structured methodology for selecting the most appropriate academic venue (e.g., SenSys, MobiSys, INFOCOM) based on the project's technical contribution and maturity.

KDD Conference Submission Pipeline Planning

brycewang-stanford/Awesome-Journal-Skills

A comprehensive project management guide for planning submissions to KDD, accounting for its unique structure of two annual submission cycles. It covers milestone tracking, cycle-choice decision matrices, managing the Resubmit loop, and planning evidence lead times from abstract to camera-ready status. Essential for complex, multi-stage data science research.

QE Project Suitability Assessment

qe-topic-selection

brycewang-stanford/Awesome-Journal-Skills

This guide helps researchers determine if their academic project is best suited for Quantitative Economics (QE) among top economic journals. It provides a structured fit test, guiding users to sharpen the substantive economic question and confirm that the quantitative method is necessary—not merely decorative—to answer it. It helps situate research by comparing QE against pure theory and method-first outlets.

Guiding Your Project To RecSys Fit

recsys-topic-selection

brycewang-stanford/Awesome-Journal-Skills

This guide helps researchers determine if their project's core contribution is genuinely centered on recommender systems. It provides a structured fit test to route the work to the most appropriate top-tier venue (RecSys, SIGIR, KDD, etc.) and select the correct conference track before starting the writing process.

Selecting Visualization Venue and Area

vis-topic-selection

brycewang-stanford/Awesome-Journal-Skills

This guide helps researchers determine if their project qualifies as a visualization contribution (beyond general HCI or ML). It provides structured criteria for choosing the best conference venue (e.g., IEEE VIS, EuroVis, CHI) and mapping the work to one of the six core visualization areas based on contribution type and evidence maturity.

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