Ferramentas

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.

In-process analytical SQL database. Its CLI queries CSV, Parquet and JSON files directly with SQL, no import or server needed, so agents can sample and aggregate large files. Officially maintained.

Creates, edits and analyzes Excel spreadsheets: formulas, formatting, charts and data cleaning, plus conversion between CSV, TSV and other tabular formats. The official Anthropic skill behind Claude's document features; source-available, not open source.

Official OpenBB MCP server exposing the OpenBB Platform's equity, ETF, macroeconomic, crypto and news data to agents; enable only the tool categories you need to save context. Needs uv locally; some data sources need your own API keys. Not investment advice.

Command-line edition of the open-source OpenBB investment research platform: query stock prices, financial statements, macroeconomic and other financial data from the terminal, and automate data pulls with Routine scripts. Officially maintained; some sources need API keys.

Teaches agents standard single-cell RNA-seq analysis with Scanpy: QC, normalization, PCA/UMAP, clustering, differential expression and plots, with ready-to-run pipeline scripts and guidance on converting Seurat and other R objects to h5ad. Needs Python 3.12+; by K-Dense.

Guides agents to the right statistical method for research data: t-tests, ANOVA, chi-square, regression and Bayesian analysis, checking assumptions, computing effect sizes and power, and reporting results in APA format. Python-based (pingouin, statsmodels); by K-Dense.

Business analytics plugin from the wshobson/agents marketplace: KPI dashboard design and data storytelling skills plus a business analyst subagent to choose metrics, plan dashboard layouts and turn data into reports executives or investors understand. Methods and templates only; no data connections.

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.

PostHog's official hosted MCP: lets agents query product analytics with HogQL, manage feature flags and A/B experiments, and investigate errors and session replays. Sign in to PostHog to authorize; tool calls are free, though a few LLM-powered tools count toward AI usage.

Official Anthropic skill for cleaning messy Excel exports: trims spaces, standardizes case and dates, converts text numbers, dedupes, and flags mixed types, garbled text and errors. Keeps originals via helper-column formulas and confirms each step. Works in Claude for Excel; local files need Python.

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.

Turns campaign or channel data into weekly, monthly or quarterly marketing reports: executive summary, key metrics and period-over-period trends, wins and misses, and next-period priorities. Connect analytics tools or just paste tables or key numbers. From Anthropic's knowledge-work-plugins.

For preclinical life sciences research: bundles MCP connectors for PubMed, bioRxiv, ChEMBL, Open Targets, ClinicalTrials and more, plus analysis skills for single-cell RNA QC, scvi-tools and nf-core pipelines. Official from Anthropic; some data sources need accounts.

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.

Data analysis plugin: writes queries in each SQL dialect, explores datasets, runs statistical tests, charts with Python and builds interactive HTML dashboards, then reviews methods and conclusions before sharing. Connects to Snowflake, BigQuery and other warehouses. Official from Anthropic.

Anthropic's official data skill that guides agents to write, translate and optimize SQL across Snowflake, BigQuery, Databricks, PostgreSQL and other warehouse dialects, including CTEs, window functions and analytical aggregations.

Google's official skill that queries account data through the Google Ads MCP server to diagnose conversion drops, falling leads and impression share lost to bids, budgets or ad rank. Needs a Google Ads account, API credentials (developer token and OAuth) and Python 3.12.

Manages BigQuery datasets, tables and jobs with the bq and gcloud CLIs, runs SQL queries and loads data, with references for client libraries, MCP and Terraform. Google's official skill; requires a Google Cloud project.

Official Lark (Feishu) skill to create and edit Lark Sheets: formulas, charts and pivot tables, conditional formatting and filters, plus import and export of local Excel/CSV, for summaries, budgets and reports. Needs lark-cli on a machine with Node.js, plus app setup and authorization.

Publishes SQLite databases as browsable, queryable web pages and JSON APIs, with SQL queries, metadata and plugins, and deploys to Cloud Run and other platforms with datasette publish. Great for data exploration and data journalism. Needs Python 3.10+.

Reads the exact position of every character, line and table cell in digital PDFs: the CLI exports layout-preserving text or CSV/JSON details, and the Python API extracts tables and form fields, ideal for invoices, statements and reports. Runs locally with Python; scans need OCR first.

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.