plwm is an X11 dynamic tiling window manager written in Prolog. It features a modular architecture with separate Prolog modules for window management logic, layouts, menus, settings, and utilities, combined with C bindings to X11 libraries via SWI-Prolog's FFI. The system processes X11 events in a main event loop, manages window state through dynamic predicates, and provides multiple interaction methods including keyboard shortcuts, dmenu/rofi menus, and a scriptable command FIFO. Key entry points include the main Prolog file (src/plwm.pl), build system (Makefile), and installation script (tools/install.sh). External dependencies include X11 libraries (libX11, libXft, libXrandr) and SWI-Prolog.
Chiasmus is a neurosymbolic verification engine packaged as a TypeScript library and Model Context Protocol (MCP) server. It bridges LLMs with formal solvers — Z3 (SMT) and SWI-Prolog (WASM) — by translating natural-language problems into template-based formal specifications that are verified with mathematical certainty. It also performs static code analysis: tree-sitter-based extraction of call graphs for TypeScript/JavaScript, Python, Go, Rust, Clojure, Scheme, Racket, and Common Lisp, followed by 16 analyses (reachability, dead code, impact, cycles, layer violations, community detection, hubs, bridges, diffs). Architecturally, the repo is a modular ESM library with an MCP server entry point (src/mcp-server.ts) exposing 11 tools over stdio (chiasmus_graph, chiasmus_map, chiasmus_formalize, chiasmus_verify, chiasmus_search, chiasmus_review, chiasmus_learn, etc.). Core subsystems: graph extraction with per-file content-hash caching and snapshot diffing; a formalization engine that selects from 8 built-in skill templates via BM25/embedding retrieval and runs an LLM-driven correction loop against the solvers; a SQLite-backed skill library that learns new templates from verified solutions; and pluggable LLM adapters (Anthropic, OpenAI-compatible, Azure, local via node-llama-cpp). Data flows: source files are parsed by tree-sitter into a CodeGraph, which can be emitted as Prolog facts for symbolic queries or analyzed natively with O(V+E) algorithms (Tarjan SCC, BFS). For verification, a problem statement is embedded, matched to a template, slot-filled by an LLM, linted, and iteratively corrected until the Z3/Prolog solver confirms the property or finds a counterexample. The benchmark suite compares Chiasmus against traditional implementations across RBAC, dependency resolution, taint analysis, workflow validation, and validation consistency. Maintenance is active (v0.1.28, CI on Node 22/24, 70+ test files covering graph extraction, solvers, MCP tools, search, and skills). The codebase is well-engineered with several genuinely reusable components — native graph algorithms, an LRU extraction cache, a BM25 index, and a tsconfig alias resolver — though some coupling exists between the extractor and the TypeScript type environment, and the vendored WASM grammars require periodic upstream syncs.
This repository is a personal knowledge base and learning collection focused on SWI-Prolog and logic programming. It contains extensive notes, tutorials, code snippets, and reusable utility modules covering a wide range of Prolog topics: language internals (data types, operators, dicts, exceptions), programming patterns (DCGs, difference lists, delimited continuations, foldl/r), puzzles, exercises, and integration with Java via JPL. The code is well-documented and includes unit tests (plunit) for many components. While not a cohesive application, the repository offers several self-contained, reusable Prolog predicates and patterns that demonstrate good Prolog craftsmanship. The primary value is as a reference and source of reusable utility code for SWI-Prolog developers.