fairozkhan10

Claude Code Trace Visualizer — AI skill for Claude Code

AI community

Trace and visualize what Claude Code does during a run: tool calls, timing, file access, retries/failures, and token/cost — a workload profiler for agentic AI.

How to install Claude Code Trace Visualizer

This entry records only its repository, not the path inside it, so there is no exact command to give. Open fairozkhan10/claude-code-trace-visualizer and copy the folder into ~/.claude/skills/, or the file into ~/.claude/agents/.

What Claude Code Trace Visualizer does

Trace and visualize what Claude Code does during a run: tool calls, timing, file access, retries/failures, and token/cost — a workload profiler for agentic AI.

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README

Claude Code Trace Visualizer

**See exactly what Claude Code did on a task** — every tool call, in order, with timing, tokens, dollars, network requests, and where it got stuck.

Point it at a session and it renders one **self-contained, offline HTML dashboard**: a timeline of tool calls, a read/explore → execute/write phase view, per-turn token & context growth, a tool-call breakdown, a file-access table, a **network-activity** panel, a **benchmark-validity audit** (flags an agent fetching a fix's provenance, instance-id leaks, work stranded in `git stash`, and writes to the graded tests — see FINDINGS finding 11), a file co-access graph, detected retry loops, a **repeated-work** panel (identical or near-identical calls the agent re-issues — a caching/optimization signal), and an errors list. No instrumentation, no services, no dependencies — it just reads the transcript Claude Code already writes.

Quick start (about 60 seconds)

No dependencies — **Python 3.9+ standard library only**.

git clone https://github.com/fairozkhan10/claude-code-trace-visualizer
cd claude-code-trace-visualizer

# 1. see a sample dashboard (synthetic data, safe to open)
open examples/example-report.html          # macOS  (Linux: xdg-open)

# 2. profile your most recent real Claude Code session
python3 -m cc_trace --latest --open

That's it. Step 2 finds your latest session under `~/.claude/projects/`, profiles it, and pops the report open in your browser.

On systems where `python` already means Python 3, you can drop the `3`. If you prefer a short command, `pip install -e .` gives you a `cc-trace` binary.

Everyday usage

# list the sessions available to profile (newest first)
python3 -m cc_trace --list

# profile a specific session (by id prefix) or a transcript path,
# and also dump the parsed data as JSON for your own analysis
python3 -m cc_trace 20814a75 -o reports/run.html --json --open

Transcripts live at `~/.claude/projects/