Tools

166 research skills maintained by K-Dense (formerly Claude Scientific Skills), spanning bioinformatics, cheminformatics, clinical research, materials and physics, including unified access to 78 public databases such as PubChem and UniProt. Works with Claude Code, Codex and Cursor.

Quant trading plugin from the wshobson/agents marketplace: quant analyst and risk manager subagents plus backtesting and risk metrics skills for strategy backtests, portfolio optimization and risk measures like VaR, Sharpe ratio and max drawdown. Needs local Python; not investment advice.

Cross-platform shell built around structured data: pipelines pass tables instead of plain text, and you can open and query JSON, CSV, TOML and more directly. Default builds include nu --mcp, which serves it to agents as an MCP server.

Trading research agent from HKU's HKUDS whose MCP server offers 70+ tools for quotes, financials, backtesting and research across A-shares, Hong Kong and US stocks and crypto. Needs local Python; HK, US and crypto research need no API key. For research only; not investment advice.

Compensation analysis for HR and managers: market pay percentiles by role, level and location, offer competitiveness checks and equity modeling; upload a pay sheet to find employees outside their band and flight risks. Without a comp data source it uses public web data, so verify. By Anthropic.

Generates people analytics reports from employee data: headcount snapshots, voluntary and involuntary attrition, diversity metrics, spans of control and flight risk, with findings and recommendations for leadership. Needs an uploaded employee CSV or a connected HRIS. Official from Anthropic.

Processes CSV, TSV, JSON and other structured data like awk, sed, cut, join and sort, but by field name, for cleaning, aggregation, format conversion and pretty-printing. The command is mlr; written in Go with no runtime dependencies.

Query cloud resources and SaaS APIs live with SQL: plugins map AWS, Azure, GCP, GitHub, Kubernetes and other services to tables you can select from directly, no ETL needed. A single binary with Postgres built in.

Creates, edits and validates reproducible Python and SQL Jupyter notebooks: organizes cells as reports or tutorials, checks conclusions against actual output and reruns top to bottom before handoff. Maintained by OpenAI in the Data Analytics plugin of openai/plugins.

Knownsec's open-source Python-use agent: describe a task in plain language and it writes and runs Python on your machine, e.g. tidying Excel files, summarizing attendance or screening resumes. Needs Python 3.11+ and a model API key such as DeepSeek; code runs locally, so back up important files.

MathWorks' official server that lets agents start your local MATLAB, write and run scripts and unit tests, and check code style and potential errors, for computing, simulation and data analysis. Needs a licensed MATLAB R2021a+ and the downloaded server binary.

Connects agents to live Jupyter notebooks: read, write, insert and execute cells and read multimodal outputs like charts, for interactive data analysis. Bring your own JupyterLab or JupyterHub; open source, maintained by Datalayer.

MathWorks' official toolkit: set up the MCP server via the MATLAB installer so agents can run code, run tests and do static checks; domain skill sets for signal processing, controls, statistics and machine learning install as Claude Code plugins. Needs MATLAB R2021a+.

Graph database MCP server from Neo4j Labs: reads the graph schema and runs read and write Cypher queries, with read-only mode, query timeouts and response token limits. Needs a Neo4j instance with the APOC plugin enabled.

HR operations plugin bundling four skills: recruiting (job descriptions, interview scorecards, funnel analysis), HRBP (talent planning, performance, employee relations), people analytics (attrition prediction, pay equity) and ops, with helper Python tools. Scripts need Python 3.

Elastic's official skills teaching agents to use Elasticsearch and Kibana correctly: index design, ES|QL queries, search relevance tuning, dashboards, observability troubleshooting and security alert triage. Currently a technical preview.

Official FinLab quant skill: lets agents use FinLab data (mainly Taiwan stocks, plus US, Japan, Korea and Hong Kong) to write stock-picking strategies, run backtests and analyze factors. Needs a FinLab account (free tier has a daily data cap), Python 3.10+ and uv. Not investment advice.