Beads (bd) is a CLI-based issue tracking system designed for AI agents and developers, using Dolt as a version-controlled SQL database backend. It provides persistent, structured memory for coding agents through features like dependency tracking, workflow automation (molecules/formulas), and JSON output for scripting. The architecture features a modular Go design with clear separation between CLI, storage abstraction (supporting both embedded and server Dolt modes), workflow APIs, and extensibility systems. Key capabilities include issue lifecycle management, dependency graphs, blocking detection, telemetry, hook-based extensibility, and integrations with external trackers like Jira, GitHub, and Notion. The system emphasizes correctness through extensive conformance testing, transactional operations, and merge-safety mechanisms for distributed clones.
This repository is a modular toolkit for academic research workflows, providing reusable 'skills' that assist with tasks such as manuscript preparation, figure generation, citation management, paper downloading, and presentation creation. Each skill is self-contained with its own workflow, documentation, and validation, while sharing common components through a nature-shared module. The system is designed for integration with AI agents (like Codex and Claude Code) and emphasizes verifiable, reproducible outputs that comply with journal-specific standards (particularly Nature Portfolio journals).
The Entire CLI (`entire`) is a production-grade command-line tool that integrates AI coding agents (Claude Code, Codex, Gemini CLI, Cursor, Copilot, OpenCode, Factory AI Droid, Pi) with Git workflows. It captures session transcripts, token usage, file changes, and agent prompts as git-backed checkpoints, enabling traceability, review, and collaboration on AI-assisted development. The CLI provides commands for session management (`session`, `resume`, `clean`), checkpoint inspection (`checkpoint list`, `checkpoint policy`), multi-agent code review (`review`, `investigate`), authentication (`auth`, `login`), and project management (`project`, `grant`). It operates as a git remote helper (`git-remote-entire`) for pushing/pulling checkpoint data via the Entire data plane. Architecturally, the system is a modular Go CLI built on Cobra, with pluggable backends for checkpoint storage (git-refs and git-branch) and agent integration. Each agent has a dedicated package under `cmd/entire/cli/agent/` that implements hooks, transcript parsing, and lifecycle management. Security is a first-class concern: file operations use `os.Root` to prevent symlink escapes (`osroot`), session IDs are validated against path traversal (`validation`), and a configurable redaction pipeline strips secrets from transcripts (`redact`). The system uses OpenAPI-generated client code (`internal/coreapi`) for control plane communication and supports multi-region deployment via cross-jurisdictional HTTP clients. The codebase demonstrates high craftsmanship with clean package boundaries, extensive test coverage (unit, integration, e2e, and benchmarks), and well-documented interfaces for extensibility. Reusable components include atomic JSON file writing, cross-platform process management (`execx`), advisory file locking (`flock`), and process liveness detection (`proclive`). The review subsystem provides a framework for multi-agent code review with structured findings, which could be adapted for other automated review workflows. While the codebase is well-maintained and actively developed, the tight coupling to many agent-specific formats and the dual checkpoint backend add maintenance surface area and complexity.
Legba is a production-grade multi-protocol credential bruteforcer, password sprayer, and enumerator written in Rust. It operates as a CLI tool with a plugin-based architecture supporting 30+ protocols (HTTP, SSH, SMB, LDAP, Kerberos, SQL variants, NoSQL, message queues, SNMP, etc.). The core system uses an async runtime (Tokio) and a global plugin inventory managed via a `register_plugin!` macro and the `Plugin` trait. Credential sources are generated by a flexible expression parser that supports wordlists, globs, permutations, ranges, and combinations. Sessions can be saved and restored in JSON format, and output supports text, CSV, and JSONL. In addition to CLI, Legba exposes a REST API and an MCP (Model Context Protocol) server, enabling AI agents to drive credential testing programmatically. A YAML recipe system allows reusable attack configurations with variable substitution.