Claude Skill

cost-breakdown

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 pla

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Download hoangsonww-claude-code-agent-monitor-plugins_ccam-analytics_skills_cost-breakdown-83d4df5.zip · 1 KB
Part of hoangsonww/claude-code-agent-monitor — 86 skills

Install

skills CLI npx skills add https://github.com/hoangsonww/Claude-Code-Agent-Monitor/tree/master/plugins/ccam-analytics/skills/cost-breakdown
Claude Code claude plugin marketplace add https://llmmart.ai/marketplace.json && claude plugin install hoangsonww-claude-code-agent-monitor@llmmart
Git git clone https://github.com/hoangsonww/Claude-Code-Agent-Monitor.git

The skills CLI installs just this skill, for any of its supported agents. Claude Code installs the whole hoangsonww/claude-code-agent-monitor collection as a plugin from our marketplace. Git is the plain clone.

Skill manifest

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.

Files (claude-code-agent-monitor)
  • agents
    • openai.yaml 269 B
      interface:
        display_name: "Cost Breakdown"
        short_description: "Break down Claude Code costs using the Agent Monitor pricing..."
        default_prompt: "Use $cost-breakdown to inspect CCAM data and complete this workflow safely."
      policy:
        allow_implicit_invocation: true
      
  • SKILL.md 3.3 KB
    ---
    name: cost-breakdown
    description: >
      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.
    ---
    
    # 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.
    

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