---
name: Model Mix
slug: model-mix
category: Data
description: Model Mix breaks down Claude Code usage by model family, showing token share, cost share, and gaps that suggest where expensive models are doing cheap work. Use it to decide routing and whether to downshift tasks to a cheaper tier.
github: "https://github.com/hoangsonww/Claude-Code-Agent-Monitor/tree/master/plugins/ccam-analytics/skills/model-mix"
language: TypeScript
stars: 933
forks: 210
install: "npx degit https://github.com/hoangsonww/Claude-Code-Agent-Monitor/tree/master/plugins/ccam-analytics/skills/model-mix ~/.claude/skills/model-mix"
installs_to: ~/.claude/skills/model-mix
source_path: plugins/ccam-analytics/skills/model-mix/SKILL.md
collection_size: 20
category_size: 668
collection_url: "https://dirskills.com/collections/hoangsonww/Claude-Code-Agent-Monitor"
added: 2026-08-22T05:20:24.462Z
last_synced: 2026-08-22T05:20:24.462Z
canonical_url: "https://dirskills.com/skills/model-mix"
---

# Model Mix

Model Mix breaks down Claude Code usage by model family, showing token share, cost share, and gaps that suggest where expensive models are doing cheap work. Use it to decide routing and whether to downshift tasks to a cheaper tier.

**Install:**

```bash
npx degit https://github.com/hoangsonww/Claude-Code-Agent-Monitor/tree/master/plugins/ccam-analytics/skills/model-mix ~/.claude/skills/model-mix
```

## README

# Model Mix

See where your tokens and dollars go by model family, and where to re-route work.

## Input

The user provides: **$ARGUMENTS**

This may be: empty (analyze the whole fleet), "today" / "this week" / a date range, or a focus like "where is Opus overused?". When empty, analyze all data from `/api/pricing/cost` and `/api/sessions`.

## Data Sources

| Endpoint | Returns |
|----------|---------|
| `GET /api/pricing/cost` | `{ total_cost, breakdown: [{ model, input_tokens, output_tokens, cache_read_tokens, cache_write_tokens, cost, matched_rule }] }` — per-model token and cost split |
| `GET /api/pricing` | `{ pricing: [{ model_pattern, display_name, input_per_mtok, output_per_mtok, cache_read_per_mtok, cache_write_per_mtok }] }` — rates per family |
| `GET /api/analytics` | `tokens` totals (total_input, total_output, total_cache_read, total_cache_write — baselines pre-summed), `agent_types` for delegation context |
| `GET /api/sessions?limit=200` | Session list — model, cwd, started_at, ended_at, inline `cost`, metadata (JSON: thinking_blocks, turn_count, total_turn_duration_ms, usage_extras) |

### How families and rates work

Map each `model` in the cost breakdown to a family from its `matched_rule` / `display_name`:

| Family | Input $/Mtok | Output $/Mtok | Cache Read $/Mtok | Cache Write $/Mtok |
|--------|-------------|--------------|-------------------|-------------------|
| Opus 4.5/4.6 | $5 | $25 | $0.50 | $6.25 |
| Sonnet 4/4.5/4.6 | $3 | $15 | $0.30 | $3.75 |
| Haiku 4.5 | $1 | $5 | $0.10 | $1.25 |

`cost = (tokens / 1M) × rate_per_mtok` summed over the 4 token types; longest `model_pattern` wins. Opus output costs ~5× Sonnet and ~5× Haiku per token, so a family's **cost share routinely exceeds its token share** — that gap is the routing signal.

## Report Sections

### 1. Token Share by Family
Aggregate `input + output + cache_read + cache_write` tokens per family from `/api/pricing/cost`. Show each family's tokens and percent of total. Cross-check the grand total against `/api/analytics` token totals.

### 2. Cost Share by Family
Sum `cost` per family. Show each family's dollar total and percent of `total_cost`. Place the cost-share % next to the token-share % so the premium gap is visible.

### 3. Cost-vs-Token Gap
For each family compute `cost_share − token_share`. A large positive gap on Opus/Sonnet signals premium spend concentration. Rank families by gap.

### 4. Expensive Model on Cheap Work
From `/api/sessions?limit=200`, find Opus/Sonnet sessions with signals of low complexity: low `turn_count`, short `total_turn_duration_ms`, few thinking_blocks, or small token footprints. List candidates that could plausibly run on a cheaper tier, with current cost and estimated cost if downshifted.

### 5. Routing Recommendations
- Quantify the savings of moving each candidate workload to the next-cheaper family (recompute cost at that family's rates).
- Note work that genuinely needs Opus (deep reasoning, long context) and should stay.
- Summarize a suggested routing policy (e.g. Haiku for mechanical edits, Sonnet for default dev, Opus for hard reasoning).

## Output

Structured Markdown with tables. Currency as USD to 4 decimal places; rates as $/Mtok; token shares and cost shares as percentages; use ▲/▼ for the cost-vs-token gap and any trend. Token counts with thousands separators.