Before the session
Keep project instructions concise, choose the relevant directory, disable unused MCP tools and prepare a focused task statement. Avoid attaching entire logs or documentation when a small excerpt answers the question.
During the session
Stop repeated tool loops, filter command output, ask for targeted file reads and summarize completed decisions. When starting a new session, carry forward unresolved requirements and the exact current state.
Local history estimator
Paste visible chat history or JSON to compare its approximate size.
For API and gateway traffic
Deduplicate stable instructions, prune tools by task and use provider caching for stable prefixes where available. Validate changes with provider-reported usage and a task-specific quality gate. Varion can automate parts of this process for eligible requests.
Measurement checklist
- Choose a representative completed task, not an artificial one-line prompt.
- Record the selected model, provider input, cached input, output, retries and final result.
- Change one optimization mechanism at a time so the cause remains visible.
- Verify required identifiers, tool calls, code changes or business fields.
- Keep passthrough available when the reduced request does not pass.
How Varion fits
Varion Token Engine is a gateway and testing platform for reducing eligible input-token waste across supported AI traffic. It reports original and provider-bound input, keeps provider charges separate, and does not claim that every request can be reduced. New verified users receive 100,000 processed input tokens and 50 local test runs.
Frequently asked questions
What is the easiest token saving?
Remove exact duplicate content and irrelevant tools. These changes are easier to verify than aggressive semantic compression.
Can I delete old history?
Only after preserving unresolved requirements, decisions and identifiers needed for the current task.