Looking at current prompts and skills, a few recurring problems show up: missing critical library versions, vague personas like you are a senior engineer, and bloated prompts that burn tokens without improving outcomes.
oh-my-agent addresses this by introducing a structured protocol to keep agents aligned with real project constraints.
Key Ideas: 1. Clarification protocol: Analyzes requirement ambiguity to decide whether to proceed, offer options, or stop for clarification.
2. Difficulty guide: Adjusts protocol depth based on task complexity.
3. Context budget: Enforces token limits per model to prevent unnecessary usage.
OpenAI’s Symphony release this March reinforced the importance of this approach. Symphony is powerful for autonomous workflows, but it performs best when the codebase is designed to be AI-friendly.
OpenAI refers to this as harness engineering: structured documentation like ARCHITECTURE.md, AGENTS.md, and WORKFLOW.md that agents can reliably interpret. oh-my-agent is built around these principles. Instead of just sending prompts, it provides the structural harness agents need to understand project context and operate autonomously.
Currently supports: Antigravity, Claude Code, Codex CLI, and Cursor.
The core idea: Using AI agents effectively isn’t about clever prompts—it’s about the engineering structure around them.
newexpand•1h ago
Structured docs like ARCHITECTURE.md help agents make better decisions upfront, but I think there's also a need for runtime feedback — knowing which agent changed what, and whether it drifted from the original task while it's still running.
How does oh-my-agent handle multi-agent scenarios where two agents might touch overlapping files?