Cursor cuts agent token costs 7% via harness: ~66% shorter system prompt, dynamic tools, cache breakpoints
Cursor (@cursor_ai) shipped agent-harness efficiency work that cut user token costs ~7% with no quality drop: trimming the system prompt ~66%, loading built-in tools on demand (prior MCP dynamic context saved 46.9% tokens in sessions that called MCP tools), explicit cache breakpoints that cut cold-cache misses 20%, and numbering only every 10th line on file reads (−1.6% cache-read tokens).
Key Takeaways
- Harness changes cut user token costs ~7% without reducing agent quality.
- System prompt trimmed ~66% as stronger models need fewer DO NOT/Important guardrails.
- Built-in tools load on demand; earlier MCP dynamic context saved 46.9% tokens on MCP-calling sessions.
- Explicit cache breakpoints cut cold-cache misses 20%; Read numbers every 10th line (−1.6% cache-read tokens).
Linked Models & Agents: