How to Cut Claude Token Costs: The Efficiency Playbook (2026)

Token spend is the silent line item: nobody budgets for it, then one heavy month arrives and suddenly everyone’s interested in context discipline. This playbook orders the fixes by real impact — the boring structural ones first, because that’s where the money is.

1. Fix what enters context (the 80% lever)

Every token Claude reads costs money before it writes a word. The biggest burners we see in audits:

• Bloated always-on context. A 3,000-line CLAUDE.md or a dozen always-loaded skills tax every single request. Skills done right load lazily — a lean trigger description up front, heavy reference files read only on demand. This is scored in our methodology for a reason.
• Redundant file reads. Agents re-reading the same files each session. Persistent memory (the Memory Management skill, 9.2/10) converts repeated re-discovery into a one-time write and cheap recalls.
• Whole-file dumps when a range would do. Reading 2,000 lines to use 40. Instruction-level discipline fixes this free.

2. Prompt caching: the discount most setups waste

Claude’s prompt caching makes repeated context dramatically cheaper — but only if your prompt structure cooperates. The rules: stable content first (system prompts, skill instructions, reference docs), volatile content last (user messages, timestamps); and mind the cache TTL — a request pattern that gaps past it pays full price on the next call.

The most common waste we find: a timestamp or session ID interpolated near the top of the system prompt, silently invalidating the entire cache every request. One-line fix, double-digit savings.

The Prompt Cache Optimizer skill automates this restructuring — it’s in our test queue with a live cache-hit-rate measurement running before we issue a verdict.

3. Compression for long sessions

Long agent sessions accumulate context like sediment. Summarize-and-continue beats carry-everything: compact the session state into a structured summary, drop the raw history, keep working. Done manually it’s tedious; the Context Compression skill packages the discipline — we’re measuring its token savings against information loss over a week of real sessions now.

4. Audit before optimizing

Guessing at token waste is its own waste. An audit answers where the spend actually goes: which sessions, which tools, which context blocks. The Token Budget Auditor reads transcripts and setups for exactly this — bloated system context, redundant reads, chatty tool loops — and we’re validating it with a before/after billing comparison.

5. Model routing (the fix everyone remembers, last)

Yes, route simple tasks to smaller models. But in every audit we’ve seen, teams reach for model routing while a broken cache and a bloated CLAUDE.md burn 3× more. Structure first, routing second.

The order of operations

Measure (audit) → fix context structure → fix caching → compress long sessions → route models. The whole Token Efficiency category tracks skills for each step as they clear testing — the only category where every verdict comes with a measured bill attached.