What is onklaud-5?

Onklaud 5 is not an AI model itself. It is a pipeline that coordinates several existing AI models together to write and review code, with the goal of getting output quality closer to a single top tier model but at much lower cost, since most of the work happens in a set of offline, non AI steps first. The pipeline starts with a step called the Ponytail Ladder, which checks a coding task against standard library functions, native language features, and existing dependencies before calling any AI model at all. The README states this resolves 57 percent of tasks with zero API cost. If that step comes up empty, the request moves through several AI stages: one model sketches an architecture, a second model writes the code based on that sketch, both models then review the code independently, and a final arbitration step reconciles any disagreements between the two reviews. A quality gate then checks the result against a 7 dimension, 10 out of 10 scoring threshold before it is considered finished. Alongside the model steps, the project includes an Immune Memory feature that stores a list of past failure patterns, currently 19 patterns across 8 categories, so the pipeline can check new tasks against known mistakes before generating anything. It also includes a context compression layer meant to keep long, multi message coding sessions from overwhelming a model's context window. The README walks through worked examples, such as building an HTTP client with retry logic or a distributed rate limiter, comparing what a single AI model would produce against what the multi step pipeline produces, including estimated dollar costs and response times for each path. It requires Python 3.10 or newer and is written in Python. It is licensed under the Business Source License 1.1, a source available license with use restrictions, which the README states will convert to the MIT License in 2030.