Data analysis, machine learning, LLM apps, and prompt design (9.1K skills)
Retrieve stock prices, historical data, financial statements, dividends, and analyst estimates from Yahoo Finance using Python. Compare multiple stocks, find stocks matching selected criteria, and present the requested figures in readable tables.
Find open-source ChatGPT and large language model tools from a project’s curated list. This local Codex entry point passes requests to awesome-chatgpt-search to find projects such as chatbots, agents, prompts, and browser extensions.
Find open-source ChatGPT and large language model projects in a bundled collection of over 2,500 entries. Filter by category or programming language, then compare relevant results with a guide organized around practical uses.
Find open-source AI tools in a bundled collection of over 2,500 repositories. Search from everyday requests, filter by category or programming language, and compare relevant options with a guide organized around practical uses.
Analyze historical stock prices to measure how long declines from local peaks to troughs lasted and how deep they were. Generate interactive HTML histograms and statistical reports to compare correction durations across sectors and company sizes.
Turn daily market observations, unusual activity, and news reactions into structured clues for investigating trading opportunities. Export hints.yaml for later analysis, with optional ideas from a language model added through an external command or a prepared file.
Assess crypto market conditions with six measures covering Bitcoin trends, altcoin participation, leverage, and momentum. Generate a 0–100 score and a market posture report using free public data or an offline snapshot, without API keys.
Analyze dated strategy returns to separate baseline exposure from performance beyond that baseline. Test stability across time and alternative comparisons, then produce JSON and Markdown reports showing how strong or fragile the evidence is.
Group raw detection records into reusable concepts before designing strategies. The skill produces a YAML file with shared conditions, supporting evidence counts, hypotheses, signals that would invalidate them, and readiness flags for strategy drafting.
Document and organize datasets in AWS catalogs by adding descriptions, owners, glossary terms, and custom metadata. The skill identifies the catalog platform first and preserves existing records when applying supported documentation and publishing changes.
Publish Amazon Redshift system logs to S3 Tables using Apache Iceberg, a table format supported by multiple query engines. Verify publishing and analyze historical query or connection activity through Athena or Redshift without loading the source cluster.
Create managed analytics tables with Amazon S3 Tables using Iceberg, a table format for data lakes. Set up columns, data types, partitions, Glue catalog integration, and access permissions, then verify the table through Athena.
Find AWS-curated prompts for AI coding agents covering prototype development, security checks, cost monitoring, and more. Also identifies separately installable agents for tasks such as quota management, database selection, and checking Bedrock model availability.
Measure and improve an AgentCore agent’s answer quality, speed, and costs. Set up evaluators, continuous monitoring, automated release checks, and CloudWatch logs and traces that show how requests move through the agent.
Analyze SageMaker Catalog metadata with SQL to count registered assets, track growth, check missing descriptions or ownership details, and compare daily snapshots to see how the catalog has changed.
Store embeddings, numerical representations of content, in Amazon S3 Vectors and search for similar items. The skill guides bucket and index setup, embedding generation, batch storage, and metadata filtering for retrieval augmented generation and infrequent queries.
Run quantum computing experiments on AWS, from choosing quantum hardware or simulators to building programs and submitting jobs. The skill also helps check device availability, compare prices, and enforce spending limits for quantum hardware tasks.
Export RDS or Aurora database snapshots to S3 as Apache Parquet, a format suited to data analysis. The workflow covers snapshot preparation, permissions, encryption, progress monitoring, and verification for analytics, backup, or migration.
Run SQL queries with Amazon Athena across Glue, S3 Tables, and Redshift catalogs. Inspect table contents, select query execution settings, and review results alongside query costs, scanned data, and execution time.
Find AWS datasets using a table name, business keyword, column name, or S3 path. Search Glue Data Catalog, S3, S3 Tables, and Redshift to return matching table references, data formats, and storage locations.
Plan and carry out a Teradata migration to Amazon Redshift, from source inventory and SQL conversion to data transfer, validation, performance comparison, and reporting. The agent uses reference guidance to generate scripts tailored to the environment.
Plan migrations and configure Amazon OpenSearch Service or Serverless for search and analytics. Explore semantic search, which finds meaning beyond keywords, analyze logs and distributed traces, and investigate incidents through natural language questions.
Plan and carry out AI model customization on Amazon SageMaker, from choosing a model and preparing data to training, evaluation, and deployment. It also guides performance optimization and diagnosis of errors in deployed model endpoints.
Build generative AI applications on Amazon Bedrock, from calling models to answering questions using retrieved documents and deploying agents. Includes guidance for content filters, model migration, prompt caching, access errors, usage limits, and cost tracking.