hoangsonww / cost-breakdown

Name: hoangsonww/cost-breakdown
Author: hoangsonww

Break down Claude Code costs using the Agent Monitor pricing engine. Shows per-model costs (input, output, cache_read, cache_write at $/Mtok rates), per-session costs, daily trends, and compaction baseline token recovery. Use when analyzing spending, comparing model costs, or planning budgets.

Version

SKILL.md

3.3 KB

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 (totalinput, totaloutput, totalcacheread, totalcachewrite — 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 cachewrite >> cacheread (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.