Cost Breakdown Skill for Claude
> 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.
Install
one command, takes just this skill from the repositorynpx skills add https://github.com/hoangsonww/Claude-Code-Agent-Monitor --skill cost-breakdownThe instruction itself
12 sections, as written by the authorCost 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.
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How to use it
Take hoangsonww/cost-breakdown from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.