This repository is a curated collection of 177+ domain-specific scientific 'skills' for AI agents, following the Agent Skills standard. Each skill is a self-contained module providing a CLI tool, documentation, and tests for a specific scientific or technical task—ranging from single-cell RNA-seq analysis (scanpy) and molecular docking (diffdock) to clinical report validation and ISO standards readiness. The architecture is a monorepo of independent skills, each with its own scripts/, references/, assets/, and tests/. Skills are designed to be safe, bounded, and reproducible: they validate inputs before execution, enforce resource limits, avoid network access unless explicitly required, and produce structured JSON reports. The repository also includes a shared test infrastructure (skill_contract) and a meta-skill (autoskill) that can automatically propose new skills from screen activity. While primarily an application library for AI agents, it has strong data/research characteristics due to its heavy use of scientific data formats and validation of research artifacts.
This repository implements a Model Context Protocol (MCP) server and CLI for searching, downloading, and reading academic papers across ~20 scholarly platforms (arXiv, PubMed, Semantic Scholar, CrossRef, OpenAlex, Google Scholar, etc.). It is primarily an application—a Python package distributed via PyPI—that exposes two entry points: an MCP server (stdio-based, compatible with Claude Desktop and other MCP clients) and a command-line interface. The architecture follows a clean two-layer design: a unified tool layer (search_papers, download_with_fallback) that orchestrates concurrent multi-source searches with deduplication, and a modular connector layer where each platform is implemented as a self-contained class inheriting from a common PaperSource abstract base. The system emphasizes a 'free-first' strategy, relying on open public APIs and optional API keys for enhanced access. It includes a fallback chain for PDF downloads (native source → OA repositories → Unpaywall → Sci-Hub) and supports full-text extraction via pypdf. The codebase is well-structured with consistent patterns (Paper dataclass, env config, retry/backoff), comprehensive test coverage (unit and e2e), and CI/CD publishing. However, some connectors are skeletons (IEEE, ACM) or not wired (ChemRxiv), and HTML scraping components are fragile to upstream changes. The last commit date is anomalously in the future (2026-08-17), but the repository shows active issue triage and community engagement.