token-burn-auditor

Measure token overhead and flag prompt bloat in Claude Code sessions.

4|1|Updated Apr 11, 2026
One-click install
npx skills add https://github.com/m2ai-portfolio/m2ai-skills-pack --skill token-burn-auditor
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: token-burn-auditor
Source: https://github.com/m2ai-portfolio/m2ai-skills-pack/tree/main/skills/token-burn-auditor
Command: npx skills add https://github.com/m2ai-portfolio/m2ai-skills-pack --skill token-burn-auditor

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Audit and minimize token waste in the Claude Code environment by measuring per-session overhead, flagging system prompt bloat, and tracking plugin/skill loading.

Core Features & Use Cases

  • Overhead measurement: quantify token usage for session startup and runtime.
  • Prompt bloat detection: identify and suggest reductions for bloated prompts and memory references.
  • Change delta reporting: compute before/after token deltas when optimizations are applied. Use Case: When optimizing a team’s Claude Code workspace, run audits before and after changes to ensure token savings and performance gains.

Quick Start

Run a token-waste audit on your current Claude Code environment to identify and reduce token overhead.

Frequently Asked Questions about token-burn-auditor

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I audit token waste in a Claude Code environment?

Token waste audits measure per-session overhead, flag system prompt bloat, and count loaded plugins and skills in Claude Code. Running an audit during session startups or ongoing workflows pinpoints areas for context reduction.

What causes high token overhead during Claude Code session startups?

High token overhead during Claude Code session startups is caused by bloated system prompts, excessive memory references, and loading too many plugins. Auditing flags these specific areas to help reduce overall context size.

How do I measure before and after token deltas when optimizing prompts?

To measure before and after token deltas, run a token-waste audit before applying changes, then run it again after trimming prompt bloat. The audit generates delta reports comparing token usage to validate performance gains.

Can I use a token linter to detect prompt bloat across different project scales?

Yes, you can use a token linter to detect prompt bloat across projects of varying scales. It works by auditing the live environment during ongoing workflow runs and startup sessions to pinpoint overhead regardless of project size.

What is the best way to reduce token overhead from loaded plugins and skills?

The best way to reduce token overhead from loaded plugins is to run an environment audit that counts active plugins and skills. This flags unnecessary loading, allowing you to disable redundant components and compute before/after savings.