Codex Usage Tracker

Unofficial project: Codex Usage Tracker is independent and is not made by, affiliated with, endorsed by, sponsored by, or supported by OpenAI. OpenAI and Codex are trademarks of OpenAI.

Use this plugin to inspect aggregate token usage from local Codex session logs.

Privacy Boundary

The index, dashboard payload, CSV export, and normal summaries are aggregate-only. They should never return prompts, assistant message text, tool outputs, pasted secrets, or raw transcript snippets.

The only exception is usage_call_context, which intentionally reads one selected record's source JSONL on demand. It requires CODEX_USAGE_TRACKER_ALLOW_RAW_CONTEXT=1 in the MCP server environment. Use it only when the user explicitly asks to inspect actual context, and mention that returned text is local, redacted, size-limited, and not persisted by the tracker.

Fast Paths

• For "Open dashboard" or similar dashboard-open requests, do not inspect repository files, plugin manifests, tool registries, git status, or local logs first. Start the live localhost dashboard with codex-usage-tracker serve-dashboard --context-api explicit --open so Refresh, Live, load-limit, and history-scope controls can call the local API. Refresh is the default for dashboard launch commands; use --no-refresh only when the user explicitly asks for a cached snapshot. Keep the server running while the user is using the dashboard. Use codex-usage-tracker open-dashboard only when the user explicitly asks for a static/offline snapshot or when the current environment cannot keep a server process running, and say that the result is static and Live requires serve-dashboard.
• For "Heaviest thread?", "Thread leaderboard", or similar thread-ranking requests, do not inspect repository files, SQLite schemas, plugin manifests, process lists, dashboard servers, or local logs manually. Use the tracker API: refresh the aggregate index, then rank threads with usage_summary(group_by="thread", limit=10, response_format="json").
• If MCP tools are unavailable for thread-ranking requests, run codex-usage-tracker refresh --json and codex-usage-tracker summary --group-by thread --limit 10 --json. The summary is already ordered by total_tokens descending.
• Answer thread-ranking requests directly from the summary rows. For the heaviest-thread question, lead with the first row's thread and total tokens; for leaderboard requests, show a compact ranked list.
• If the CLI command is missing for dashboard-open requests and you are already inside the source checkout, use PYTHONPATH=src .venv/bin/python -m codex_usage_tracker.cli serve-dashboard --context-api explicit --open. Use the source-checkout open-dashboard fallback only for static/offline snapshots or when a long-running server cannot be kept alive.
• If the CLI command is missing for thread-ranking requests and you are already inside the source checkout, use PYTHONPATH=src .venv/bin/python -m codex_usage_tracker.cli refresh --json and PYTHONPATH=src .venv/bin/python -m codex_usage_tracker.cli summary --group-by thread --limit 10 --json.
• If neither command is available, say briefly that the tracker CLI is not on PATH and ask the user to run codex-usage-tracker setup or reinstall with pipx.
• Keep dashboard-open narration minimal: one short progress note if needed, then the localhost URL, or if falling back to a static file, the file path plus a note that Live requires serve-dashboard. Do not narrate plugin discovery.

Suggested Usage Questions

When the user wants ideas, suggest concrete aggregate investigations:

• Look through my usage for token waste.
• Find calls where context got bloated.
• Show me where caching failed.
• Which threads are draining the most?
• What changed recently?
• Find expensive calls worth opening in the investigator.
• Check whether model or effort choice is wasting tokens.
• Build a strict-privacy summary I can share.

Route these through usage_report_pack, usage_calls, usage_threads, usage_summary, and usage_call_detail before considering raw context.

Common Workflows

• Refresh the index before answering usage questions.
• Use usage_doctor when setup, plugin discovery, MCP launch, dashboard output, or pricing estimates look wrong.
• Use usage_summary for high-level totals by date, model, effort, cwd, thread, or session.
• Use usage_query for stable JSON rows filtered by date, project, model, effort, thread, pricing status, token minimums, or Codex credit minimums.
• Use usage_status for dashboard/index freshness, active/scoped/total row counts, latest refresh timestamp, and observed allowance windows.
• Use usage_calls for the same aggregate Calls table rows as the React dashboard, including pagination, filters, derived pricing status, and credit confidence.
• Use usage_call_detail for the aggregate Call Investigator payload for one record_id. Use usage_call_context only for explicit raw-context requests.
• Use usage_threads for the same aggregate Threads table rows as the dashboard.
• Use usage_report_pack for dashboard report cards plus compact evidence rows when the user wants less cloudy "what should I inspect?" output.
• Use usage_dashboard_recommendations when the dashboard-specific recommendation payload is more useful than the older markdown-oriented recommendation report.
• Use usage_recommendations when the user asks what to inspect next or wants ranked action items by aggregate severity.
• Use usage_summary presets today, last-7-days, by-model, by-cwd, by-thread, and expensive for common requests.
• Use usage_pricing_coverage when the user asks whether costs are fully priced or which models use estimated or missing pricing.
• Use session_usage for per-call and per-turn detail for one session.
• Use usage_call_context for one selected model call when the user asks to load actual logged context on demand.
• Use most_expensive_usage_calls to identify high-token calls and aggregate efficiency signals.
• Use privacy_mode="redacted" or privacy_mode="strict" for MCP tools, or the CLI global option --privacy-mode strict before a subcommand, when the user plans to share dashboards, CSV, JSON, screenshots, or support bundles.
• Use generate_usage_dashboard when the user wants a visual hoverable report, including flat calls, threaded-by-thread views, parent-thread latching for spawned subagents, auto-review attachment details, an active-only default, and explicit all-history archived-session opt-in.
• Use export_usage_csv when the user wants local spreadsheet-friendly data.
• Use update_usage_pricing_config when the user wants cost estimates based on OpenAI-published text-token pricing. This refreshes the local pricing cache and does not send local usage data anywhere. Internal Codex labels may include explicitly marked best-guess estimates when no public pricing row exists.
• Use init_usage_pricing_config only when the user wants a manual local pricing template or override file.
• Codex credit estimates are aggregate-only and use bundled or locally configured Codex rate-card values. Direct model matches are exact; aliases and inferred labels are marked estimated.
• Use init_usage_allowance_config only when the user wants a local allowance template for manually copied 5-hour or weekly remaining usage from Codex Usage or /status.