Search Results for "evidence"

...It runs beside existing tools rather than hiding inside a specific agent runtime, so users can apply it to a chosen repository or isolated worktree. The workflow is built around clarifying requirements, planning before mutation, turning approved plans into goals, and tracking evidence until completion. It includes tmux-backed execution options for coordinating parallel workers when a task is large enough to benefit from them. Gajae-Code is useful for developers who want coding agents to behave less like single-prompt assistants and more like disciplined project collaborators. Its main value is giving AI coding work a clearer loop for interviews, plans, goals, execution checks, and evidence.

REA (Reverse Engineer Anything) is an open-source, AI-powered reverse engineering toolkit that enables developers and AI agents to analyze software applications, native binaries, and runtime behavior. The platform uses the Model Context Protocol (MCP) to connect AI coding assistants with tools for inspecting compiled code, application structures, and software functionality. It supports reverse engineering of native executables, JavaScript and Electron applications, .NET assemblies, Android...

...The system runs on the user’s own infrastructure and keeps its orchestration visible through tmux. A command-line interface manages setup, health checks, queues, and workstation configuration. OpenRig also includes skills, evidence tracking, reusable packages, and support for persistent team workflows. It is aimed at developers who want several coding agents collaborating as a stable group rather than operating as isolated assistants.

...GitHub repositories can be cloned locally so Pi can inspect real source files instead of relying on rendered pages. Video support includes transcripts, visual descriptions, timestamped frame extraction, and questions about on-screen content, while evidence tools help collect passages for manual claim verification.

...The framework supports multiple operational modes, including debugging, planning, security auditing, and release validation. It can run unattended for extended periods, producing logs of experiments and improvements. This approach transforms software development into an iterative, evidence-driven optimization process rather than manual trial and error.

...Built-in subagents can work in parallel or continue tasks independently while returning results to a parent agent. A continual harness stores memories, skills, prompts, and reusable agent specifications that can improve through evidence-backed refinement. Daemon-backed sessions survive terminal disconnections and can be resumed later. Automatic compaction, persistent goals, schedules, heartbeats, and autonomous execution help maintain progress across extended tasks.

...It exposes search, fetching, crawling, extraction, research, monitoring, and autonomous gathering through MCP, REST, command-line tools, and SDKs. Its search engine combines results from multiple adapters using rank fusion, local reranking, and explainable evidence scores. The fetch router can escalate from ordinary HTTP requests to browser automation when it encounters dynamic pages or anti-bot challenges. Crawling supports breadth-first, depth-first, sitemap, and mapping modes while respecting robots.txt and domain rate limits. Results, embeddings, and configuration are stored locally, and the core tools require no account or paid API key. ...