Fable 5 burns tokens fast. I found an cost tracker for it

A new open-source tool called cost-xray captures the actual local API traffic for AI coding agents Claude Code and Codex, attributing tokens and costs down to individual sources like system prompts, tool schemas, and MCP blocks. The tool installs as a transparent local proxy requiring no API keys or configuration changes, and provides a terminal UI that lets developers drill from session-level totals to per-call costs, including cache read/write splits. This granularity allows developers to see not just how much a coding session cost, but exactly which components drove those costs.

See what your AI coding agent actually sends to the API — and what each part costs. Most usage tools read local logs. That shows the total cost of a call or session, but it misses the request-time context assembled before the model is invoked: system prompts, tool schemas, MCP blocks, tool results, cache reads/writes, and previous thinking blocks. cost-xray captures the actual local API traffic for Claude Code and Codex, then attributes tokens and dollars back to the sources inside the request. It shows not just how much a turn cost, but why it cost that much. Home — every session by agent · project · session, with token and dollar totals | Drill a session — context-window occupancy top and per-source cost, down to each MCP server bottom | - A supported coding agent — Claude Code https://github.com/anthropics/claude-code or Codex https://github.com/openai/codex - macOS or Linux - No API keys, no account, no config changes to your agent — capture is a transparent local hop curl -fsSL https://raw.githubusercontent.com/tigerless-labs/cost-xray/master/install.sh | bash The installer asks which agent s to capture — Claude Code, Codex, or both — and prompts even under curl … | bash . Skip the prompt e.g. CI : set COST XRAY AGENTS=claude|codex|all . Already cloned the repo? Run ./install.sh . Then open a new terminal and run claude / codex exactly as before — capture is automatic, no flags and no base-URL change. It's forward-only : runs started in that new shell are captured, not past history. Open the live TUI from anywhere: cx Capture runs as a background service auto-start on boot, self-healing, port-adaptive and doesn't change what your agent does, its results, or its cost — pause anytime with cx stop . See docs/install.md /tigerless-labs/cost-xray/blob/master/docs/install.md for systemd details, GUI agents Cursor base-URL setup , manual no-systemd mode, and troubleshooting. cx open the live cost-xray TUI from any directory cx status services' state, live ports, sessions captured cx stop stop monitoring — proxies down; agents run direct uncaptured cx start resume monitoring cx restart restart the proxies after a config change cx install re install — authoritative: installs the chosen agents, removes the rest cx uninstall remove services + shell wrappers keeps captured data cx is the whole CLI and works from any directory. Change port/upstream by editing ~/.cost-xray/env , then cx restart . ./run.sh <cmd from the repo still works too — cx just calls it for you from anywhere. In the TUI, drill from the top down: agent → project → session → category → MCP server → tool → per-turn call → the real output . Every cell carries its cache split read / write / fresh / output $ . | Agent | Status | Capture | |---|---|---| | Codex https://github.com/openai/codex The wire is decoded by a thin per-agent adapter — the only place code forks by agent docs/architecture.md /tigerless-labs/cost-xray/blob/master/docs/architecture.md ; per-agent capture + tokenizer notes under docs/providers/ /tigerless-labs/cost-xray/blob/master/docs/providers/README.md . Adding an agent is one small module; anything speaking the Anthropic or OpenAI-Responses wire shape is close to drop-in. cost-xray traces every token's cost — split into fresh / cache-read / cache-write / output — to the source that caused it, and down to the individual call : the cost of this Read invocation and its output, not a session sum. Everyone else aggregates — a request- or session-level total, at most grouped by tool type "Read cost $X this session" . As far as we've found, nothing else prices below the tool, call by call. What is taking space in the context window right now — system prompt, every tool schema, MCP servers, messages, and generated output — decomposed into source-level rows. Prompt caching makes a stable 40k-token schema block cheap on cache read, but it still crowds out the code and conversation that matter; cost-xray shows you the occupancy, not just the bill. Configured servers and tools that are injected into every request's prefix but never actually called. They pay their tool-schema overhead on every turn — cost-xray flags the dead weight. Claude's tokenizer is private — no official or open-source tokenizer exists — and calling Anthropic's count tokens API for everything would add load and hit its limits. So for Claude, cost-xray uses an estimator plus proportional calibration: tiktoken sizes each part, the parts it mis-sizes most thinking, tool schemas get targeted corrections — pinned with count tokens when you're logged in, a fixed ratio otherwise — and the rest is scaled so the calibrated total matches the provider's own usage . The total, and therefore the bill, is exact; only the split between sources in the same request is approximate. We benchmark those residuals continuously CONTRIBUTING.md /tigerless-labs/cost-xray/blob/master/CONTRIBUTING.md and they're small enough for attribution work. Coming soon: an opt-in exact mode — every part sized by full count tokens differencing — manually enabled, for users who need maximum per-source precision. The wrappers are per-command and self-healing: if the proxy is down, the wrapper restarts it and routes through; if it can't, the agent runs direct — never broken. Stop monitoring anytime with cx stop agents then run direct . cost-xray keeps the complete raw API traffic — but a long session re-sends its whole history every turn, so the capture is hugely repetitive. We deduplicate it: each unique block message, schema, tool result is stored once, with a tiny per-turn delta. Full per-turn bytes rebuild on demand. Disk stays small even across million-token sessions. Log-based tools ccusage, codeburn, and similar are excellent at local-first session analytics: they read local transcripts, classify turns by tool usage, and price the session by model, day, or task. That answers how much did I spend . cost-xray answers the lower-level question: what bytes did the model actually receive, and which source owns those tokens? The difference is the data source. Log readers see the transcript after the agent has run — but the system prompt, injected tool schemas, MCP schemas, reminders, and provider-added blocks are assembled at request time and never written to the transcript . In real coding-agent requests, that invisible prefix can be roughly half the context or more. cost-xray reads the raw API request, so it can compute source-level tokens and attribute cost to schemas, MCP servers, tools, and message buckets. | Question | Log / usage tools | cost-xray wire capture | |---|---|---| | How much did the session cost? | Yes | Yes | | Which task/tool was active? | Yes | Yes | | System prompt and injected schemas visible? | No | Yes | | How many tokens does each tool schema occupy? | No, schemas aren't in logs | Yes | | Which MCP server is dead weight in the prefix? | Estimate | Exact | | Cache read/write/fresh dollars per source/tool? | No, usage is request-level | Yes, by span and cache boundary | | Live view of the current request window? | No | Yes | cost-xray surfaces the data; you read the story. A few patterns worth knowing: | Signal you see | What it might mean | |---|---| | A 40k-token MCP schema block on every turn | A configured server crowding the prefix — drill it to see if any tool was called | | Cache-read dollars dwarf fresh input | Stable prefix is working; the spend is in what's new each turn | | Repeated cache-write on the same source | The prefix is being rewritten — something upstream of it changed | | Thinking tokens dominate output cost | Long reasoning turns; check whether they earned their keep | | A tool's schema costs more than the tool is ever used | Candidate to drop from the agent's tool-set | Big tool result rows on Read / Bash | Uncapped output bloating the window — cap it at the source | These are starting points, not verdicts. One experimental session looking odd is fine; the same pattern across weeks of work is a config issue. cost-xray runs mitmproxy as a local capture hop and keeps all analysis off the request path. agent ──HTTP──▶ mitmproxy ──HTTPS──▶ model API │ └── redacted raw request/response → ~/.cost-xray/sessions/ │ └── materializer → TUI / cost attribution Capture. Claude Code uses reverse-proxy mode via a base-URL override — no certificate. Codex locked HTTPS endpoint uses a forward proxy plus a scoped local CA, trusted only by the codex command and never added to your system trust store. The wrapper self-heals: if the proxy is down it restarts and routes through, otherwise it runs the agent direct — capture never breaks your agent. Local & private. The proxy binds to 127.0.0.1 and sends no telemetry. Authorization , API keys, cookies, and secret-looking body fields are redacted before anything hits disk. Everything stays under ~/.cost-xray/ — delete that directory to clear it. Off the hot path. The proxy only writes redacted bytes; a separate materializer tokenizes and prices later, so analysis never steals latency from live relay. Raw is the source of truth — every view rebuilds from it on demand. See docs/install.md /tigerless-labs/cost-xray/blob/master/docs/install.md for setup and docs/architecture.md /tigerless-labs/cost-xray/blob/master/docs/architecture.md for the full pipeline. Capture built on mitmproxy https://github.com/mitmproxy/mitmproxy ; the SSE/redaction approach was adapted from llm-interceptor https://github.com/chouzz/llm-interceptor . Pricing data from LiteLLM https://github.com/BerriAI/litellm . README structure inspired by codeburn https://github.com/getagentseal/codeburn . Built by Tigerless Labs.