tokenwise
Measurement-driven model router for Claude Code. Routes Haiku/Sonnet/Opus per task class, logs every routed task with real $ numbers, and A/B tests cheaper tiers before you trust the savings.
Best use case
tokenwise is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Measurement-driven model router for Claude Code. Routes Haiku/Sonnet/Opus per task class, logs every routed task with real $ numbers, and A/B tests cheaper tiers before you trust the savings.
Teams using tokenwise should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/tokenwise/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How tokenwise Compares
| Feature / Agent | tokenwise | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Measurement-driven model router for Claude Code. Routes Haiku/Sonnet/Opus per task class, logs every routed task with real $ numbers, and A/B tests cheaper tiers before you trust the savings.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# TokenWise — Measurement-Driven Model Router ## Overview A Claude Code skill that auto-routes subtasks to the cheapest model that can handle them (Haiku for grunt work, Sonnet for scoped reasoning, Opus only for synthesis), then logs every routed task to a local NDJSON with real token + cost numbers. Includes an A/B test subcommand that runs the same task across multiple tiers and scores quality, so the routing decisions are verified against the user's real workload — not estimated. Anthropic's own bug tracker (Issue #27665) reports 93.8% of Max-subscriber Claude Code tokens flow to Opus. Existing routers (claude-router, wshobson, VoltAgent) either pin models statically or route by vibes-based heuristics with no measurement. TokenWise fills the measurement gap. ## When to use - Cutting Claude Code token spend without sacrificing output quality - Validating whether Haiku/Sonnet is "good enough" for a specific task class before trusting auto-routing - Auditing where Opus tokens are actually being burned - Logging per-session cost data for finance or chargeback ## Subcommands - `/tokenwise:install` — guided installer with diff preview, automatic backups, and `--dry-run` mode - `/tokenwise:report` — per-session token + cost summary vs all-Opus baseline - `/tokenwise:summary [--week|--month|--all]` — historical aggregate with trend - `/tokenwise:ab "<task>"` — A/B test the same task at multiple tiers, generates a markdown comparison - `/tokenwise:undo` — restore CLAUDE.md / settings.json from backup ## Routing taxonomy | Tier | Model | Task class | |---|---|---| | Mechanical | Haiku 4.5 | file reads, grep, format, rename, simple edits, doc lookups | | Scoped reasoning | Sonnet 4.6 | single-file refactor, scoped research, test writing | | Synthesis | Opus 4.7 | architecture decisions, multi-file refactor, security review | Safety caps: - Haiku never spawns further subagents - Max spawn depth = 2 - Subagents that need a smarter model return to parent — they never escalate on their own - Tasks under 100 chars with no file context run inline (subagent overhead > savings) - Subagent context >30k tokens bumps a tier ## Privacy Zero telemetry. All logs in `.tokenwise/log.ndjson` local to the project. Task descriptions truncated to 80 chars and stripped of file contents before logging. No analytics endpoint exists in the source. ## Install In any Claude Code session: ``` /plugin marketplace add CodeShuX/tokenwise /plugin install tokenwise@tokenwise ``` Then run `/tokenwise:install` and follow the guided prompts. ## Limitations - Token counts approximate to ±2% vs Anthropic billing - A/B test mode costs extra tokens (one task × N tiers) — intentional one-time validation - Anthropic-only by design (use LiteLLM or OpenRouter for cross-vendor) - Subagent `model:` param has known silent-fail bugs on some Claude Code builds — skill probes for this at install and refuses to configure if routing is broken ## Source - Repo: https://github.com/CodeShuX/tokenwise - License: MIT - Author: CodeShuX
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