Skill456 repo starsupdated 2d ago

cost-breakdown

The cost-breakdown Claude Code skill provides detailed cost analysis for Claude API usage by querying an Agent Monitor pricing engine. It accepts time periods like "today" or "last 30 days", session IDs, or budget limits, then retrieves pricing rules and token consumption data to generate reports on cost by model, top expensive sessions, daily spending trends, and token efficiency metrics including cache hit rates.

View source Repository: Claude-Code-Agent-Monitor

Install in Claude Code

Copy

git clone --depth 1 https://github.com/hoangsonww/Claude-Code-Agent-Monitor /tmp/cost-breakdown && cp -r /tmp/cost-breakdown/plugins/ccam-analytics/skills/cost-breakdown ~/.claude/skills/cost-breakdown

Then start a new Claude Code session; the skill loads automatically.

Definition

SKILL.md

# Cost Breakdown

Detailed cost analysis from the Agent Monitor's pricing engine.

## Input

The user provides: **$ARGUMENTS**

This may be: "today", "this week", "last 30 days", a session ID, or "budget $50/week".

## Data Sources

| Endpoint | Returns |
|----------|---------|
| `GET /api/pricing` | `{ pricing: [{ model_pattern, display_name, input_per_mtok, output_per_mtok, cache_read_per_mtok, cache_write_per_mtok }] }` |
| `GET /api/pricing/cost` | Total cost: `{ total_cost, breakdown: [{ model, input_tokens, output_tokens, cache_read_tokens, cache_write_tokens, cost, matched_rule }] }` |
| `GET /api/pricing/cost/{sessionId}` | Per-session cost with same breakdown shape |
| `GET /api/sessions?limit=200` | Sessions list — each includes inline `cost` field (bulk pricing) |
| `GET /api/analytics` | Token totals (total_input, total_output, total_cache_read, total_cache_write — baselines pre-summed), daily trends |

### How costs are calculated

The pricing engine matches model names against `model_pattern` using SQL LIKE (e.g. `claude-sonnet-4-5%` matches `claude-sonnet-4-5-20250514`). **Longest pattern wins** for specificity. Cost per model:

```
cost = (input_tokens / 1M) × input_per_mtok
     + (output_tokens / 1M) × output_per_mtok
     + (cache_read_tokens / 1M) × cache_read_per_mtok
     + (cache_write_tokens / 1M) × cache_write_per_mtok
```

Token counts are **effective totals** = `current + baseline` (baselines preserve pre-compaction tokens that would otherwise be lost when the transcript JSONL is rewritten).

### Default pricing tiers (seeded on first run)

| 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 |

## Report Sections

### 1. Cost by Model
Table from `/api/pricing/cost` breakdown — each model with 4 token counts + cost. Highlight which pricing rule matched.

### 2. Cost by Session (Top 10 Most Expensive)
From sessions list with inline `cost` — sort descending. Show session name, model, duration, cost.

### 3. Daily Cost Trend
Cross-reference `daily_sessions` with per-session costs to compute daily spend. Show 7/30-day trend with direction arrows.

### 4. Token Efficiency Analysis
- **Cache hit rate**: `total_cache_read / (total_cache_read + total_input) × 100` — higher = more efficient
- **Compaction baseline recovery**: Tokens preserved via baseline columns (tokens not lost to compaction)
- **Output/input ratio**: Balanced ratio indicates good prompt efficiency

### 5. Cost Optimization Opportunities
- Sessions where cache_write >> cache_read (poor cache reuse)
- Expensive models used for simple tasks (check subagent_type vs model)
- Sessions with many compactions (context overflow = wasted tokens)

## Output

Structured Markdown with tables. Currency as USD to 4 decimal places. Include total and per-model subtotals.