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Ponytail is an AI-agent ruleset and plugin system that pushes coding assistants toward simpler, smaller, and less over-engineered solutions. It is built around the idea that the best code is often the code that does not need to be written. Before generating new code, it encourages the agent to check whether the feature is necessary, whether the standard library already solves it, whether the platform has a native capability, or whether an existing dependency can do the job. The project...

...It indexes codebases into a persistent knowledge graph so agents can understand architecture, symbols, call chains, routes, and cross-service relationships without reading every file repeatedly. The project uses tree-sitter AST analysis across 158 languages and adds Hybrid LSP type resolution for major languages like Python, TypeScript, JavaScript, Go, C#, Java, Rust, C, and C++. It is built for speed, with average repositories indexed in milliseconds and structural queries answered in under one millisecond. It ships as a single static binary for macOS, Linux, and Windows with no shared library dependencies. It also includes semantic search, BM25 search, graph visualization, auto-indexing, and cross-repository intelligence.