Agent Config
An open-source configuration framework for AI coding agents that wraps coding agent tools with sets of skills, rules, workflows, and quality checks, providing acceptance mechanisms such as a production validator.
Timeline (last 90 days)
Agent Config is an MIT-licensed open-source project with no paid tier, positioned as "your AI engineering system"; it is a collection of skills, rules, workflows and quality checks layered on top of Claude Code and several other coding tools, rather than a new coding model.
The production validator provided by Agent Config can be used standalone to specifically verify whether an agent's claimed "completion" actually holds.
Agent Config's design includes "look before you leap" (the agent analyzes the codebase before changing code), an end-to-end workflow (from planning and implementation to testing and review), multi-perspective review (approaching from the four angles of bugs, security, tests and code quality), memory and project context, on-demand loading of skills and rules, and support for multiple coding tools.
The author of Agent Config says the project has grown beyond his initial vision, that he is working hard to avoid turning it into a "token-burning monster," and candidly admits he is still figuring out where added complexity is genuinely useful and where it is purely disruptive.
The author believes that when the model's ability to write code is no longer the bottleneck, the engineering focus shifts to how to verify the agent's output, and Agent Config's answer is to build the checking process into the agent's workflow, making "self-checking" a default action rather than an after-the-fact remedy.
All Facts (5)
Agent Config is an MIT-licensed open-source project with no paid tier, positioned as "your AI engineering system"; it is a collection of skills, rules, workflows and quality checks layered on top of Claude Code and several other coding tools, rather than a new coding model.
50%UnverifiedThe production validator provided by Agent Config can be used standalone to specifically verify whether an agent's claimed "completion" actually holds.
50%UnverifiedAgent Config's design includes "look before you leap" (the agent analyzes the codebase before changing code), an end-to-end workflow (from planning and implementation to testing and review), multi-perspective review (approaching from the four angles of bugs, security, tests and code quality), memory and project context, on-demand loading of skills and rules, and support for multiple coding tools.
50%UnverifiedThe author of Agent Config says the project has grown beyond his initial vision, that he is working hard to avoid turning it into a "token-burning monster," and candidly admits he is still figuring out where added complexity is genuinely useful and where it is purely disruptive.
50%UnverifiedThe author believes that when the model's ability to write code is no longer the bottleneck, the engineering focus shifts to how to verify the agent's output, and Agent Config's answer is to build the checking process into the agent's workflow, making "self-checking" a default action rather than an after-the-fact remedy.
50%