by luoyuctl
Local-first Rust TUI/CLI for auditing AI coding-agent sessions: cost, tokens, latency, failures, and health|本地优先 Rust TUI/CLI,审计 AI 编程 Agent 会话的成本、Token、延迟、失败与健康度
# Add to your Claude Code skills
git clone https://github.com/luoyuctl/agenttraceLast scanned: 7/14/2026
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"file": "README.md",
"line": 82,
"type": "remote-install",
"message": "Install command (remote install script piped to a shell — review the source before running): \"curl -sL https://raw.githubusercontent.com/luoyuctl/agenttrace/master/install.sh\"",
"severity": "low"
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"status": "PASSED",
"scannedAt": "2026-07-14T06:10:39.698Z",
"npmAuditRan": true,
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}agenttrace is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by luoyuctl. Local-first Rust TUI/CLI for auditing AI coding-agent sessions: cost, tokens, latency, failures, and health|本地优先 Rust TUI/CLI,审计 AI 编程 Agent 会话的成本、Token、延迟、失败与健康度. It has 119 GitHub stars.
Yes. agenttrace passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.
Clone the repository with "git clone https://github.com/luoyuctl/agenttrace" and add it to your Claude Code skills directory (see the Installation section above).
agenttrace is primarily written in Rust. It is open-source under luoyuctl on GitHub, so you can review or fork the full source.
Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh agenttrace against similar tools.
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Based on votes and bookmarks from developers who liked this skill
agenttrace is a local-first terminal TUI and report generator for AI coding-agent session history. It reads Claude Code, Codex CLI, Gemini CLI, Qwen Code, Cline, Aider, Cursor exports, Hermes Agent, OpenCode, OpenClaw, Pi, Oh My Pi, Kimi CLI, Copilot-style logs, and generic JSON/JSONL traces, then helps with two daily jobs: see what multiple agents spent across cost, tokens, and time; and diagnose why a task ran slowly.
One agenttrace binary provides both interfaces: run it without a report action to open the TUI, or pass flags such as --sessions and --overview for CLI output.
AI coding agents now behave like small build systems: they call tools, retry, stall, and spend tokens while you only see the final answer.
agenttrace reads the logs your agents already write and puts cost-heavy or slow sessions first.
It helps you answer:
These screenshots and figures are a redacted sample of the latest 500 real local sessions captured for the v0.7.1 source tree. They are not --demo output, current telemetry, or test fixtures.
agenttrace
| Overview | Critical sessions |
|---|---|
| Session detail | Diagnostics |
|---|---|
That local run found:
AGENTTRACE v0.7.1
| Signal | What agenttrace found |
|---|---|
| Analyzed sessions | 500 |
| Total tokens | 4.0B |
| Estimated cost | $2.6K |
| Tool failure rate | 2.9% |
| Critical sessions | 2 |
| Average health | 77.7% |
Install the latest public release with your package manager. Check the installed
version with agenttrace --version.
# macOS and Linux
brew install luoyuctl/tap/agenttrace
# macOS, Linux, and Windows (requires Node.js 18+)
npm install -g @zack78/agenttrace
Windows:
winget install --id Luoyuctl.AgentTrace --exact
The package names above become available once the corresponding release has been published. Manual installs remain available without a package manager:
curl -fsSL https://raw.githubusercontent.com/luoyuctl/agenttrace/master/install.sh | sh
cargo install --git https://github.com/luoyuctl/agenttrace agenttrace
iwr -useb https://raw.githubusercontent.com/luoyuctl/agenttrace/master/install.ps1 | iex
agenttrace
# Audit raw token components, normalized pricing, and fallback confidence.
agenttrace --audit --range 30d -f json
# Optional local model aliases and per-million-token price overrides.
AGENTTRACE_PRICING_FILE=pricing-overrides.json agenttrace --audit -f json
# Rank evidence-backed actions by severity and estimated impact.
agenttrace --recommend --range 30d -f json
# Inspect observed MCP invocations. Loaded-server coverage is intentionally
# reported as unavailable unless the source log actually records it.
agenttrace --mcp-governance --range 30d -f json
# Review cross-session context, cache, repeat-read, and read/write trends.
agenttrace --context-trends --range 30d -f json
# Correlate local Git commit timestamps with sessions (heuristic, read-only).
agenttrace --delivery-evidence --range 30d -f json
pricing-overrides.json accepts aliases plus per-million-token prices:
{"aliases":{"provider/raw-model":"my-model"},"prices":{"my-model":{"input":1,"output":2,"cw":0,"cr":0}}}
--overview now includes scope, parse and pricing confidence, cost audit,
prioritized recommendations, MCP governance, context trends, and delivery
signals in JSON, Markdown, and HTML output. All cost and delivery fields are
explicitly estimates or heuristics; they are not provider billing or proof that
a commit reached main.
| Need | agenttrace gives you |
|---|---|
| Historical spend review | Sessions grouped across projects, agents, and models with Today/7d/30d/All ranges |
| Data confidence | Report scope, per-source coverage, parse skips, cache hits, unknown sources/models, pricing fallbacks, and latest observed session |
| Cost audit and action plan | Token component rates, pricing source/status, estimated cost confidence, and prioritized, evidence-backed remediation suggestions |
| Governance trends | Canonical project grouping, observed MCP invocation governance, cross-session context/cache/read-write trends, and read-only Git delivery correlation |
| Honest capability levels | Detailed, Aggregate, or Limited per session so missing event-level evidence is never presented as a complete trace |
| Privacy-safe steps | Tool-step metadata and duration when the source provides call IDs and timestamps; no prompt, response, result, or tool-argument body is stored in steps |
| Slow-task diagnosis | Latency stats, long gaps, hanging sessions, retry loops, slow tools, large params, and context pressure |
| Regression evidence | Local baseline comparison when supplied, incident timelines, and conservative tool authority categories in reports |
| First-session triage | Sort and filter by cost, duration, health, failures, anomalies, model, source, or text search |
| Shareable evidence | JSON, Markdown, and self-contained HTML reports |
| Local-first inspection | No hosted backend required |
Listed in these open source projects:
Parser PRs are welcome. A good parser contribution usually includes:
crates/agenttrace-core/src/parser.rsRun before sending a PR:
cargo test
cargo build --release -p agenttrace
target/release/agenttrace --doctor
See CONTRIBUTING.md for the full contribution flow.
MIT © 2026 agenttrace contributors