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agent loop

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Basic Information

Agent Loop is a framework for AI-driven software development that coordinates a team of specialist AI agents via an orchestrator to handle tasks from high-level planning and architecture to coding, testing, and deployment. The repository documents core concepts, roles, and workflows for using the system through simple textual commands. It defines an orchestrator that delegates work and multiple specialist agents such as Architect, Builder, Tester, Researcher, Reviewer, Debugger, Planner, Scope Analyst, Security Analyst, and Code. The README explains command-driven interactions like /plan, /build, /test and shows an example end-to-end workflow. It also captures core agent principles in a CLAUDE.md reference, emphasizing delegation, context awareness, test-driven development, and a structured thinking process before execution. The project is intended to guide users in orchestrating agent-based software engineering workflows rather than providing a single monolithic AI.

Links

App URL
https://github.com/Saik0s/agent-loop
Github Repository
https://github.com/Saik0s/agent-loop/blob/main/README.md

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App Details

Features
A command-driven orchestration model that accepts simple commands such as /plan, /spec, /build, /tdd, /test, /analyze, /review, /fix, and /update-project-docs. A clear separation of roles with specialist agents for architecture, building, code optimization, debugging, testing, research, reviewing, scope analysis, and security. An Orchestrator that delegates tasks and composes plans into actionable subtasks. Test-Driven Development and quality-first practices that require failing tests before implementation. Project-aware planning where agents search the codebase for conventions and patterns before changing code. Support for producing conventional commit messages and updating documentation. Researcher-driven citations for verifiable findings. Core thinking primitives such as think, think harder, and ultrathink that guide agent reasoning and stepwise execution.
Use Cases
Agent Loop helps teams and individual developers run repeatable, auditable AI-assisted engineering workflows by structuring work across specialized agents and an orchestrator. It reduces manual coordination by translating high-level goals into detailed, file-aware plans and assigning those tasks to appropriate specialist agents. The framework enforces best practices like TDD, code reviews, security analysis, and context-aware modifications so changes remain idiomatic to the project. It can generate specifications, tests, fixes, refactors, and commit messages, and it supports end-to-end feature delivery from planning to documentation updates. The inclusion of a Researcher agent with citations and an emphasis on testing and analysis helps maintain quality and traceability of decisions. The README provides concrete command examples and an example workflow to onboard users.

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