Open source alternatives to cosmosdb-datamodeling
24 open source AI Skills apps to use instead, best rated first.
Top picks
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github-ops
Launchgithub-ops is an agent skill from the ECC collection by affaan-m, listed on skills.sh. It manages a GitHub repository with a focus on community health, CI reliability and the experience of contributors. It covers triaging issues by classify
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opensource-pipeline
Launchopensource-pipeline is an agent skill from the ECC collection by affaan-m, listed on skills.sh. It prepares a private project for safe public release through a three-stage pipeline. The fork stage strips secrets from a copy. The sanitise st
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andrej-karpathy-skills
Launchandrej-karpathy-skills is a single CLAUDE.md file from the multica-ai project that is meant to improve how Claude Code behaves on coding tasks. It is derived from Andrej Karpathy's public observations about LLM coding pitfalls. The file dis
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microsoft/markitdown
Launchmarkitdown-mcp is the MCP server package for MarkItDown, Microsoft's tool for converting many file formats to Markdown for language models. It is a lightweight server that runs over stdio, Streamable HTTP or SSE, and exposes one tool, conve
Open source
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od-contribute
Launchod-contribute is an agent skill in the OpenDesign project that provides a guided, one-click contribution flow to the OpenDesign repository, written so that people without a coding background can send a real pull request. It is locked to the
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- G
github-deep-research
Launchgithub-deep-research is an agent skill from the DeerFlow project that researches a single GitHub repository in several rounds and writes a report in Markdown. It is for requests that need more than a README summary, such as a comprehensive
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About cosmosdb-datamodeling
cosmosdb-datamodeling
Comprehensive guide
cosmosdb-datamodeling is an agent skill from the github/awesome-copilot collection that guides the design of Azure Cosmos DB NoSQL data models. It works through structured requirements gathering and then an aggregate-oriented design. The agent first captures the application's requirements, the access patterns, the volumetrics and the concurrency and workload characteristics, and records them in a cosmosdb_requirements.md file. It then designs the data model using the core philosophy and design patterns of Cosmos DB, saving the result to a cosmosdb_data_model.md file. The skill sets a firm limit on the questions it asks: one question at a time, or at most three related questions. It also includes a warning for massive-scale workloads, such as more than 10,000 writes per second or batch processing of millions of records in a short period. For those, the agent must ask about data binning and chunking, the minimum number of actual write operations, and how total data size affects physical partitions before it designs anything. The skill is useful for teams starting a Cosmos DB application who want the access patterns settled before the model is fixed, since changing a partition key later is costly. The requirements file should be agreed with the people who own the workload. The skill is installed with the skills CLI from the github/awesome-copilot repository. Its skills.sh page showed about 8.7K installs and passing results from three security audits at the time of the scan.
- Price
- Free
- Made by
- github
- Category
- AI Skills
- Website
- github.com/github/awesome-copilot/cosmosdb-datamodeling