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98.71% less repeated context for coding agents.
Pitch

Qarinah gives Codex and Claude Code a local, cited project memory. It compiles the decisions and evidence needed for the next task instead of replaying the whole history - with a reproducible 98.71% reduction in repeated context.

Description

Overview

Qarinah is a powerful local project memory and context compiler designed for coding agents, offering a significant reduction in the amount of repeated context needed during interactions. This innovative tool claims an impressive 98.71% reduction in estimated input-context, compressing 442,113 input tokens down to just 5,682 through highly efficient context management. Its effectiveness is backed by benchmarks that demonstrate a 77.81:1 context compression ratio, ensuring that coding tasks are not only efficient but also governable and evidence-linked.

Key Features

  • Local-First Design: Ensures high reliability and performance without relying on external servers.
  • Evidence-Linked Memory: Connects every coding decision to its source, enabling clear accountability and traceability.
  • Graph-Aware Compilation: Utilizes a sophisticated graph structure to maintain project integrity and provide comprehensive context.
  • Governance-Ready: Meets the stringent requirements for project governance with built-in controls for data retention and access permissions.

Technical Highlights

Qarinah's architecture allows coding agents to efficiently manage project memory while ensuring that decisions and evidence are clearly linked. With Qarinah, the captured project history isn't played back in its entirety; instead, only relevant, bounded context is compiled for the task at hand, significantly increasing operational efficiency. The following are key aspects of its functionality:

Evidence and Context Management

  • Each selected piece of context links back to its original source, allowing for easy verification of historical decisions and reducing cognitive overhead.
  • Metadata-only capture ensures that unnecessary data is not stored, keeping memory clean and focused.

Performance and Cost Efficiency

  • Compared to traditional coding practices, Qarinah drastically cuts down on the input context costs, making it much more economical for agents to operate. With the estimated input-context cost significantly lowered, it is designed to optimize workflow in both small and large coding tasks.

Architecturally Robust

  • Qarinah employs a layered architecture where event management, metadata capture, and retrieval systems work cohesively, ensuring optimized performance without relying on a cloud-based infrastructure.
  • The system can be exported in a recognized format supporting interoperability with other tools and frameworks, allowing organizations to leverage the captured project memories easily.

Getting Started

To begin using Qarinah, follow these setup commands:

npm install --save-dev qarinah
npx qarinah init .

Once set up, you can start recording decisions and managing project memory effectively by leveraging Qarinah's advanced querying and evidence linking capabilities.

Conclusion

Qarinah represents a shift towards enhanced productivity in coding environments. It transcends traditional memory management systems by focusing on evidence-linked context and efficient project memory, ultimately carving out a path for coding agents to thrive with greatly reduced overhead. Explore more by visiting the Qarinah website or diving into the documentation.

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