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TOKEN PIRANHA
"Bite the bloat. Keep your tokens."
How much of your AI context is being consumed before you do useful work? Scan your Claude Code, Codex CLI, MCP servers, and skills configurations in memory to detect duplicate instructions, oversized schemas, and per-turn context tax.
The Feeding Frenzy: Context Distribution
Solid = Initial Per-Turn Overhead | Dim = On-Demand FootprintBefore / After Configuration Comparison
Measured per-turn context overhead reductionToken Predators (High-Impact Bloat Sources)
0 FoundContext Diet: Actionable Optimization Plan
Ranked by per-turn token impact and confidence. Apply adjustments manually; V1 does not alter local files.
| Rank | Action | Target Source | Est. Savings | Recommendation |
|---|
Limits: token counts are offline estimates (about 5% mean error versus OpenAI cl100k/o200k on our test corpus, individual files up to roughly 20%); they are not official Claude counts. Savings figures describe per-turn prompt size, not your bill. Scanning runs entirely in your browser; known secret formats are redacted, but redaction cannot catch every secret, so review exports before sharing.
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