Files
AgentHub/plugins/agenthub-analytics/skills/cost-breakdown/SKILL.md
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nntrivi2001 17d56d0e01 refactor!: rebrand CCAM to AgentHub
Clean break, no compatibility alias. Renames the product name, the CLI
binary (`ccam` -> `agenthub`), the env var prefix (`CCAM_` ->
`AGENTHUB_`), the Prometheus metric namespace (`ccam_*` ->
`agenthub_*`), the tmux session prefix (`ccam-lane-<id>` ->
`agenthub-lane-<id>`), the per-repo runtime profile directory
(`.ccam/profile` -> `.agenthub/profile`), the lanes state root
(`~/.claude/ccam-lanes` -> `~/.claude/agenthub-lanes`), the bundled
plugins (`plugins/ccam*` -> `plugins/agenthub*`) and their slash
commands (`/ccam-doctor` -> `/agenthub-doctor`, `/ccam:*` ->
`/agenthub:*`).

Because there is no alias, an existing install has to be updated by
hand: rename its `.ccam/profile` directory and any `CCAM_*` variables,
and reinstall the plugin under its new name.

Two other name families are deliberately left alone here, since they are
not just strings: the `Claude-Code-Monitor` repository/marketplace name,
and the `agent-dashboard` npm package plus its `~/.claude/agent-dashboard`
runtime directory, which holds the live database and needs a migration
rather than a rename.

Verified: server 1406/1406, client 459/459, `grep -i ccam` clean across
tracked files, `openapi.yaml` regenerated (95 paths, unchanged count).
2026-09-07 12:09:15 +07:00

3.3 KiB
Raw Blame History

description
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.