acaprino/cc-usage
plugins/cc-usage/skills/cc-usage/SKILL.md
Analyze Claude Code token usage, costs, billing blocks, and tool activity from local session data. TRIGGER WHEN: the user asks about their usage, costs, burn rate, or wants a usage dashboard/report. DO NOT TRIGGER WHEN: the task is outside the specific scope of this component.
tools
Updated Apr 20, 2026
$ install --global
skillsauthnpx skillsauth add acaprino/anvil-toolset cc-usageInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
Security Scan Results
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
3
Scanners Passed
9
Scanners in report
Clean
TrivyContainer and dependency vulnerability scanner
95%
Clean
SemgrepStatic code analysis for vulnerabilities
95%
Clean
mcp-scan (Snyk)Model Context Protocol security validation
95%
Skipped
Snyk (dep)Open source security scanning
50%
Skipped
Socket.devSupply chain security analysis
50%
Skipped
VirusTotalMulti-engine malware detection
50%
Skipped
CrowdStrikeAdvanced threat intelligence
50%
Skipped
OSV-ScannerOpen Source Vulnerability database check
50%
Skipped
OWASP Dep-Check
50%
Last scanned: Apr 20, 2026, 4:02 AM15.9s2 files scanned
SKILL.md
- name:
- cc-usage
- description:
- >
- TRIGGER WHEN:
- the user asks about their usage, costs, burn rate, or wants a usage dashboard/report.
- DO NOT TRIGGER WHEN:
- the task is outside the specific scope of this component.
Claude Code Usage Analyzer
Analyze Claude Code session data to generate usage reports with token counts, cost estimates, billing block tracking, tool usage stats, and per-project breakdowns.
Inspired by paulrobello/par_cc_usage.
How it works
Claude Code stores session data as JSONL files in:
~/.config/claude/projects/(Linux/macOS primary)~/.claude/projects/(legacy Unix)%USERPROFILE%\.claude\projects\(Windows, default)- Custom path via
CLAUDE_CONFIG_DIRenv var (all platforms)
The script parses these files, extracts assistant message token usage, deduplicates by request ID, and computes:
- Total token usage (input, output, cache)
- Cost estimates using Anthropic pricing
- 5-hour billing block tracking with burn rate
- Per-model breakdown (Opus vs Sonnet)
- Tool usage frequency
- Per-project and per-session stats
- Daily usage trends
Usage
Run the analysis script:
python plugins/cc-usage/skills/cc-usage/scripts/cc_usage.py
Options
| Flag | Description |
|------|-------------|
| -d, --days N | Number of days to analyze (default: 7) |
| -p, --project NAME | Filter by project name (substring match) |
| --no-block | Hide current billing block section |
| --no-projects | Hide project breakdown |
| --no-tools | Hide tool usage stats |
| --no-sessions | Hide recent sessions list |
| -n, --top N | Number of top items per section (default: 10) |
| --json | Output raw JSON instead of formatted markdown |
Examples
# Last 7 days, full report
python cc_usage.py
# Last 30 days, filter to one project
python cc_usage.py -d 30 -p "my-project"
# Quick overview, no details
python cc_usage.py --no-tools --no-sessions -n 5
# Machine-readable JSON output
python cc_usage.py --json
When to invoke
Run this script for the user when they ask about:
- Their Claude Code usage or costs
- Token consumption or burn rate
- Current billing block status
- Which tools they use most
- Which projects consume the most tokens
- Usage trends over time
Execute via Bash:
python <path-to-script>/cc_usage.py [options]
Then present the markdown output directly to the user -- it renders as formatted tables.
Report sections
- Overview - Total tokens, messages, cost for the period
- Current Billing Block - Active 5-hour block with remaining time, burn rate, projected cost
- Usage by Model - Token and cost split between Opus, Sonnet, etc.
- Tool Usage - Most-used tools with visual bar chart
- Projects - Per-project token and cost breakdown
- Recent Sessions - Most recently active sessions
- Daily Breakdown - Day-by-day token and cost trend with bar chart
Data sources
The script reads Claude Code's native JSONL format. Key fields extracted:
message.usage- token counts (input, output, cache_creation, cache_read)message.model- model identifier for pricing tiermessage.content[].type == "tool_use"- tool call trackingcostUSD- native cost field (used when available, falls back to calculated)requestId- deduplication keytimestamp- for time-based analysis
Pricing
Pricing is defined in a single source of truth: scripts/cc_usage.py (see the MODEL_PRICING table near the top). To update prices, edit that table -- this document intentionally does not duplicate the numbers to avoid drift.
When costUSD is present in the JSONL data, that value takes priority over calculated estimates.
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