ECC Agent Harness for AI Coding Assistants

GitHub - affaan-m/ECC: The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.

Source: other · unknown Saved: 2026-06-02 Tags: other Display: ECC Agent Harness for AI Coding Assistants — Configuration framework adding persistent memory, skills, and security guardrails to AI coding agents like Claude Code and Cursor.

TL;DR

ECC (Enhanced Claude Code / agent harness) is a performance optimization system and configuration framework for AI coding agents — including Claude Code, OpenAI Codex, Opencode, and Cursor — providing structured skills, instincts, persistent memory, and security hardening layers. It acts as a 'harness' that wraps and augments AI agent environments to improve output quality and reliability. AI coding agents are powerful but inconsistent — they lack persistent context, enforced best practices, and security guardrails out of the box. ECC addresses this by supplying a reusable, research-first harness that standardises agent behaviour, injects domain skills and instincts, and maintains memory across sessions, making AI-assisted development more predictable and production-ready.

What the post showed

Key claims from transcript:

• (no transcript available)

What it actually is

• What: ECC (Enhanced Claude Code / agent harness) is a performance optimization system and configuration framework for AI coding agents — including Claude Code, OpenAI Codex, Opencode, and Cursor — providing structured skills, instincts, persistent memory, and security hardening layers. It acts as a 'harness' that wraps and augments AI agent environments to improve output quality and reliability.
• Who built it / maintained by: affaan-m (individual open-source contributor on GitHub; full identity not publicly disclosed)
• Status: stable
• Why it matters: AI coding agents are powerful but inconsistent — they lack persistent context, enforced best practices, and security guardrails out of the box. ECC addresses this by supplying a reusable, research-first harness that standardises agent behaviour, injects domain skills and instincts, and maintains memory across sessions, making AI-assisted development more predictable and production-ready.
• How it compares to alternatives:
• aider
• continue.dev
• Cursor rules/.cursorrules configs
• OpenDevin
• Sweep
• Cline
• Plandex
• GitHub stars: 203,871 · License: MIT · Archived: no

Links

• Repo: https://github.com/affaan-m/ecc

Kickstarter guide

Clone the repository with git clone https://github.com/affaan-m/ecc.git and review the README for agent-specific setup instructions. Configure your target agent (e.g. Claude Code or Cursor) to load the ECC harness by following the provided skill and memory configuration files. Customise the instincts and security policies to match your project's requirements, then run your agent as normal — ECC layers its optimisations transparently on top.