Does this skill require external dependencies?

Yes, it requires the 'jq' utility to be installed on your system to parse the JSON session data received from Claude Code.

Can I display metrics other than tokens and cost?

Yes, the script has access to various session data including model names, lines of code changed, and timing metrics, all of which can be formatted and displayed.

How do I customize the appearance of the status line?

You can modify the provided shell script to change color thresholds, adjust the progress bar width, or include additional metadata fields from the session JSON.

Will this impact my terminal's performance?

The script is designed to be highly efficient and runs locally on each render cycle. As long as you avoid adding network calls to the script, it will not noticeably affect performance.

Context Window Status Line

Name: Context Window Status Line
Author: sejas

bysejas

•

분석 및 모니터링

Monitors real-time context window usage, token consumption, and session costs directly within the Claude Code terminal footer.

The Context Window Status Line skill provides a customizable dashboard for Claude Code, enabling developers to visualize critical session metrics such as token counts, API costs, and context window saturation. By integrating a dynamic footer bar into the terminal interface, users can track resource usage and session performance in real-time, helping to optimize prompt efficiency and manage API expenditures during long development sessions. It offers granular insights into input/output tokens, cache hits, and performance timing, all through a non-intrusive terminal-based UI.

주요 기능

01Live session cost calculation in USD with four-decimal precision

02Real-time tracking of input, output, and cached tokens

03Visual context window progress bar with color-coded thresholds

04Interactive diff counters displaying lines of code added and removed

05Performance metrics including total wall time and API response duration

062 GitHub stars

사용 사례

01Tracking the financial cost of complex AI coding sessions to manage project budgets

02Monitoring token usage during large-scale refactors to prevent unexpected context compaction

03Optimizing prompt strategies by observing cache hit rates and token efficiency in real-time

주요 기능

01Live session cost calculation in USD with four-decimal precision

02Real-time tracking of input, output, and cached tokens

03Visual context window progress bar with color-coded thresholds

04Interactive diff counters displaying lines of code added and removed

05Performance metrics including total wall time and API response duration

062 GitHub stars

사용 사례

01Tracking the financial cost of complex AI coding sessions to manage project budgets

02Monitoring token usage during large-scale refactors to prevent unexpected context compaction

03Optimizing prompt strategies by observing cache hit rates and token efficiency in real-time