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AI Usage Dashboard
analytics dashboard for Claude Code session activity.
ai-sessions is a local-first analytics dashboard for Claude Code sessions. It parses JSONL files from ~/.claude/projects/, calculates usage, cost, token, tool, and productivity metrics, and serves a React dashboard with live WebSocket updates. It includes REST APIs, drill-down views, KPI cards, token trends, session explorer, tool usage insights, hourly activity charts, context health tracking, and prompt optimization insights to help developers and teams reduce AI spend.
ai-sessions is a local-first analytics dashboard for Claude Code session activity.
It parses Claude session JSONL files from ~/.claude/projects/, computes usage/cost/productivity metrics, and serves a React dashboard with live updates over WebSocket.
What it does
Loads historical Claude Code sessions into an in-memory store.
Aggregates token, cost, tool, project, and daily activity metrics.
Streams near-real-time updates when session files change.
Exposes REST APIs for dashboard data and detailed drill-down views.
Serves a React + Vite UI from the same Go binary.
Who this helps
This dashboard is useful for:
Individual developers who want to understand AI usage, token burn, and cost over time.
Power users of Claude Code who want to improve prompt quality and session hygiene.
Tech leads / engineering managers who need visibility into usage patterns, project focus, and productivity windows.
Anyone optimizing AI spend who wants to track cache efficiency and reduce repeated context costs.
Widget ideas this dashboard gives you
If you are building your own analytics UI, this project shows practical widget patterns you can reuse:
KPI cards: sessions, total spend, output tokens, cache efficiency.
Token trend chart: cache vs input/output views, with date-range toggles.
Session explorer table: searchable session list plus detail drawer.
Tool usage panel: top tools with clickable sample drill-down.
Hourly activity chart: peak coding/agent activity by hour.
Conversation breakdown table: prompt/response previews with output, context %, cost, and time.
Context health panel: context-window fill tracking with warning states.
Prompt insights card: actionable suggestions to reduce token waste and improve quality.
Live update banner: real-time feedback when new session data arrives.
About AI Usage Dashboard on Product Hunt
“analytics dashboard for Claude Code session activity.”
AI Usage Dashboard was submitted on Product Hunt and earned 1 upvotes and 1 comments, placing #90 on the daily leaderboard. ai-sessions is a local-first analytics dashboard for Claude Code sessions. It parses JSONL files from ~/.claude/projects/, calculates usage, cost, token, tool, and productivity metrics, and serves a React dashboard with live WebSocket updates. It includes REST APIs, drill-down views, KPI cards, token trends, session explorer, tool usage insights, hourly activity charts, context health tracking, and prompt optimization insights to help developers and teams reduce AI spend.
On the analytics side, AI Usage Dashboard competes within Productivity, Analytics, Developer Tools and GitHub — topics that collectively have 1.4M followers on Product Hunt. The dashboard above tracks how AI Usage Dashboard performed against the three products that launched closest to it on the same day.
Who hunted AI Usage Dashboard?
AI Usage Dashboard was hunted by Arunkumar Sivasubramanian. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of AI Usage Dashboard including community comment highlights and product details, visit the product overview.
Arunkumar Sivasubramanian