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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.

Exploratory Data Analysis

exploratory-data-analysis

K-Dense-AI/scientific-agent-skills

Performs bounded local exploratory analysis of supported scientific files, including CSV/TSV/JSON profiles, optional NumPy, HDF5, FASTA/FASTQ and image metadata inspection, audits, and EDA report scaffolds.

Get Available Resources

get-available-resources

K-Dense-AI/scientific-agent-skills

Detects host inventory including CPU, memory, disk, scheduler, container, and accelerator limits for resource-aware planning. Produces a redacted JSON snapshot without stress tests or assuming hardware usability. Compatible with Python 3.11+ on Linux, macOS, or Windows.

NetworkX Graph Analysis

K-Dense-AI/scientific-agent-skills

Create, analyze, and visualize complex networks in Python with NetworkX 3.x. Build graphs from data, run algorithms like shortest paths, PageRank and centrality, detect communities, generate synthetic networks, and read/write GraphML, JSON or edge-list files.

PufferLib RL Environment Framework

K-Dense-AI/scientific-agent-skills

Version-aware guidance for PufferLib reinforcement-learning environments, vectorization, policies, PuffeRL training, evaluation, and safe checkpoint review. Adapt Gymnasium/PettingZoo environments to published PufferLib 3.0.0 or work with redesigned native 4.0 source line with Python 3.10+ and Torch 2.9+. Includes safe defaults for CPU-only, network-free tools with strict JSON output and dependency-free bundled CLIs.

pydicom DICOM Dataset Toolkit

K-Dense-AI/scientific-agent-skills

Read, inspect, write, transform, and safely preflight local DICOM datasets and pixel data with pydicom 3.0.2. Covers metadata, transfer syntaxes, compression plugins, frames, private elements, JSON export, and bounded de-identification review with strict PHI safety boundaries.

Pyzotero Reference Library Automation

K-Dense-AI/scientific-agent-skills

Manage Zotero reference libraries programmatically with the pyzotero Python client and Zotero Web API v3. Retrieve, create, update and delete items, collections, tags and attachments; search libraries and export BibTeX or CSL-JSON citations for research automation workflows.

Anima Debug Bundle Generator

anima-debug-bundle

jeremylongshore/claude-code-plugins-plus-skills

This utility generates a comprehensive JSON debug bundle for troubleshooting and support requests related to the Anima SDK. It collects vital information, including environment details, Figma API connectivity status, and verifies the Anima SDK generation capabilities. Use it when filing support tickets or debugging code generation issues.

BambooHR API Migration And Upgrade Guide

bamboohr-upgrade-migration

jeremylongshore/claude-code-plugins-plus-skills

This comprehensive guide details the process of managing BambooHR API changes, addressing breaking changes, and migrating from legacy patterns. It covers critical tasks such as converting XML to JSON, updating deprecated field usages (e.g., 'bestEmail' to 'workEmail'), and implementing robust testing and rollback strategies for seamless integration.

Advanced Anthropic Messages API Patterns

clade-model-inference

jeremylongshore/claude-code-plugins-plus-skills

This guide covers advanced usage of the Anthropic Messages API. Learn how to implement real-time streaming responses, utilize system prompts for persona control, process visual inputs (Vision), and enforce structured data output (JSON). This is essential for building sophisticated, robust, and multi-modal Claude-powered applications.

Cloud LLM Provider Regression Testing

cloud-provider-regression-test

SharpAI/DeepCamera

Automates comprehensive regression testing for all enabled cloud Large Language Model (LLM) providers. This includes verifying core connectivity, standard chat completion, structured JSON output, and Server-Sent Events (SSE) streaming capabilities. Essential for ensuring the reliability and stability of multi-cloud AI integrations in a CI/CD pipeline.

Sync AI Agents to Azure AI Foundry

foundry-agent-sync

github/awesome-copilot

This skill creates and synchronizes prompt-based AI agents directly into Azure AI Foundry using the Agent Service REST API. By defining agents in a local JSON manifest, the skill registers them server-side, making them instantly available for evaluation and invocation within the Foundry ecosystem. It is essential for deploying, updating, or managing AI agents at scale within the Azure cloud environment.

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