by quarqlabs · Agent Tool · ★ 233
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Quarq Agent Local memory. Hybrid retrieval. Self-correcting reasoning. Benchmark-grade recall. Quarq Agent is a memory-first AI agent built by QuarqLabs for long-context personal intelligence, grounded recall, temporal reasoning, quantitative reasoning, and tool use. It is designed as an open, inspectable alternative to memory agents such as Hermes or OpenClaw, with a stronger emphasis on durable local memory, strict attribution, self-correcting retrieval, and benchmark-grade long-term recall. The current local benchmark run is in progress on LongMemEval-S and is tracking in the 99.6% to 99.7% range. The latest checked report in shows yes, no, or , with the full 500-question run still continuing. Why Quarq Exists Most agents can chat. Fewer can remember. Almost none can remember carefully. Quarq Agent is built around a simple idea: memory is not just vector search. A serious memory agent needs to know what a memory means, when it happened, what numbers belong to, which entity a fact is attached to, when evidence is incomplete, and when it must search again instead of guessing.
| Stars | 233 |
| Forks | 21 |
| Language | Python |
| Category | Agent Tool |
| License | Apache-2.0 |
| Quality Score | 67.8698367479663/100 |
| Last Updated | 2026-06-04 |
| Created | 2026-05-24 |
| Platforms | python |
| Est. Tokens | ~53k |
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agent-oss is A recursive evidence-gated cognitive runtime for memory-native AI agents, combining hybrid retrieval, temporal reasoning, async learning, and plug-and-play tools.. It is categorized as a Agent Tool with 233 GitHub stars.
agent-oss is primarily written in Python.
You can find installation instructions and usage details in the agent-oss GitHub repository at github.com/quarqlabs/agent-oss. The project has 233 stars and 21 forks, indicating an active community.
agent-oss is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
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