udaysharmadev/Gravitas

What it solves

Coding agents often fail due to poor process rather than lack of intelligence. They frequently edit files they haven't read, make broad changes for narrow tasks, run tests inconsistently, or claim to finish tasks without providing proof. Gravitas enforces a disciplined engineering workflow to ensure that AI-generated code is grounded in evidence and verified by actual execution.

How it works

Gravitas acts as a reliability runtime that sits between your AI agent and your code. It implements six core "invariants"—rules that require the agent to read files before editing, stay within a declared scope, and provide fresh, executed proof for every change. If an agent tries to finish a task without passing these automated checks, the system blocks completion. It uses a combination of portable "Agent Skills" and optional host-specific plugins to monitor tool calls and verify that the agent's actions match its claims.

Who it’s for

This tool is for developers and teams who use AI coding agents and want to increase the reliability of their output. It is particularly useful for those who want to enforce strict engineering standards—such as read-before-write and evidence-based verification—without changing the underlying AI model.

Highlights

• Enforces a strict "read-before-write" policy to prevent blind file edits.
• Requires fresh, executed validation results to prove a task is complete.
• Blocks exact retries of failed actions to prevent repetitive, wasteful loops.
• Uses machine-readable plans to scale effort based on the risk of the task.
• Provides a tamper-evident ledger to track evidence and verify session integrity.
• Works with existing agents via portable skills or host-specific plugins.