Audits Claude Code context window consumption across agents, skills, MCP servers, and rules. Identifies bloat, redundant components, and produces prioritized token-savings recommendations.
SkillScore86Maintained
Automatic
◆AI Engineer pack
Last verified 8/21/2026
What it changes
Passed 18 of 21 test cases with the skill, and 9 of 21 without it.
Without skill41%
With skill86%
Checks it passed that the model alone missed
Estimates the token count as 1,300 tokens
Estimates the token footprint as 2,000 tokens
Estimates the schema overhead at 7,000 tokens
and 8 more in the full report
10 fixed9 passed either way3 still failing0 broke
Pass-rate lift
+45 pp
Tokens
+18%
Agent turns
0%
Response time
-57%
Model gemini-3.6-flashMeasured 8/21/2026v719 of 22 cases passed with skill · 21 comparable
Tokens, turns and time describe resource use, not a dollar price.
See it in action
One of 10 test cases the skill fixed. Same model, same prompt, with and without the skill.
1 of 10
Prompt
I have a dense JSON file containing 8,000 characters with no prose commentary. According to token estimation guidelines for code-heavy files, how many tokens does this file consume?
What was checked, without and with the skill
Checked
Without skill
With skill
Estimates the token footprint as 2,000 tokens
Missed
Passed
case-05 · gemini-3.6-flash · 8/21/2026 · answers are capped and redacted
What's inside
The instructions your model reads when the skill loads.
SKILL.md136 linessingle file
Context Budget
Analyze token overhead across every loaded component in a Claude Code session and surface actionable optimizations to reclaim context space.
When to Use
Session performance feels sluggish or output quality is degrading
You've recently added many skills, agents, or MCP servers
You want to know how much context headroom you actually have
Planning to add more components and need to know if there's room