atuljha23 Token economy
Three things drive cost in Claude Code: context size, cache hit rate, and model choice. Most waste comes from one of these being misconfigured and left alone.
Model tiering — match the model to the task
| Task shape | Right model |
|---|---|
| Format fix, rename, small refactor, comment tweak | Haiku — ~15× cheaper than Opus, fast enough to feel instant |
| Routine feature work, bug fix, test writing, reviewing a small diff | Sonnet — the default; 5× cheaper than Opus |
| Architectural decision, cross-file refactor, debugging a subtle bug, reviewing a large diff | Opus — use when you need the reasoning, not by default |
Claude Code's /fast or model selection lets you pick. Don't use Opus by reflex for a typo fix.
Cache hygiene — the 80% lever nobody talks about
Anthropic caches your prompt prefix for 5 minutes. A stable prefix = the next turn reads from cache at ~10% of input cost. A prefix that changes each turn = full price every time.
What busts cache:
- Timestamps in CLAUDE.md, in skill content, or in hook output
- Session IDs / UUIDs interpolated into system prompt
- Rotating "quotes of the day", random greetings
- MCP servers that return time-varying schema metadata
What preserves cache:
- CLAUDE.md that doesn't change day-to-day
- Skill/rule content that's additive, not mutating
- Hook
additionalContextthat's deterministic for a given input - Turning off MCP servers you don't need (every schema change invalidates cache)
How to check: /holocron:cost — the cache hit rate line. Below 50% is a signal; above 70% is healthy.
Read discipline — the most common leak
Claude's Read tool pulls whole files by default. A 2000-line file is ~8k tokens. Do that 5 times in a session and you've spent ~40k tokens reading the same file repeatedly.
Pattern:
Grepto find the relevant range (cheap — returns only matching lines)Readwithoffset+limitfor the range you identified
Holocron's read-budget.js hook nudges this on files > 500 lines, but the discipline has to be yours.
MCP pruning — one-time setup, ongoing savings
Every MCP server's tool schemas ship to the model on every turn. An unused MCP server costs you tokens forever.
Audit with /holocron:mcp-audit. Disable servers you don't actively use. Two or three MCP servers is usually plenty; ten is a tax.
Subagent isolation — don't pollute the main context
Research / exploration / "find me all the callers" work bloats the main transcript with files and noise you won't need after. Run it in a subagent:
Use the Explore agent to find how `authenticateUser` is called across the repo.
The subagent's findings come back as a summary; its exploration stays in its own context. Main session stays lean.
Transcript discipline
Claude Code auto-compacts near the context limit, but compaction is lossy — it summarizes, and summaries forget things. Better:
/holocron:handoffat logical boundaries — write state to a file, start fresh on the next task- For long-lived work:
/holocron:plan→ plan file → execute → handoff. The plan file acts as durable memory.
Subtle things
- Large tool outputs stay in the transcript. A single 20k-token tool result inflates every subsequent turn's input cost until compaction.
Writeof a large file re-reads context. Edit prefers over Write for big files.- Don't paste log output. Summarize, grep, or point to a file.
- Emojis are multi-token. Harmless unless you're generating content heavy in them.
Anti-patterns
- Running Opus on every turn "to be safe"
- Full-file Reads on generated/vendored files (
dist/,node_modules/, generated protobufs) - Keeping MCP servers installed that you tested once and never used again
- Timestamp-injecting SessionStart hooks (looking at you, naive
console.log(new Date())in a hook that emitsadditionalContext)
How to know it's working
Run /holocron:cost weekly. Healthy numbers:
- Cache hit rate > 60% (70%+ if you're disciplined)
- Median session cost under your per-session budget
- Per-model split skews Sonnet-heavy, with Haiku for small things, Opus for reasoning
If those aren't true, @cost-analyst can tell you why.