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Her · हेर - Claude Code 会话分析工具

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Her · हेर - Claude Code 会话分析工具

TL;DR · AI 摘要

Her是一款分析Claude Code会话的工具,通过解析JSONL文件帮助用户理解操作和风险。

核心要点

  • Her可自动解析Claude Code会话的.jsonl文件,标记风险操作如生产环境部署
  • 工具完全本地运行,数据不离开本地环境且会自动删除
  • 内置Ask Her Copilot可追溯工具调用并展示具体操作步骤

结构提纲

按章节快速跳转。

  1. Her是一款用于分析Claude Code会话的可视化工具

  2. 通过解析JSONL文件还原会话过程并标记风险操作

  3. 识别工具调用路径和资源消耗情况

  4. 基于Nemotron-Mini-4B模型的本地化部署方案

  5. 完全离线运行且数据自动销毁的隐私保障

  6. 支持单会话分析和多会话项目视图对比

思维导图

用一张图看清主题之间的关系。

查看大纲文本(无障碍 / 无 JS 友好)
  • Claude Code分析工具
    • 核心功能
      • 会话追溯
      • 风险标记
    • 技术实现
      • 本地运行
      • 数据销毁
    • 使用场景
      • 单会话分析
      • 多会话对比

金句 / Highlights

值得收藏与分享的关键句。

#Claude Code#分析工具#本地运行
打开原文

Her · हेर — _Marathi for “detective.”_ A detective for your Claude Code sessions.

Try it here: Her on Hugging Face

Every Claude Code session leaves a trace — a .jsonl file with every turn, tool call, and token. But in practice, that trace is write-only. Rarely anyone reads 4,000 lines of JSON to figure out _why the agent reached for production_, where the context budget actually went, or which subagent quietly burned half the run.

Her reads it for you.

The premise is simple: drop a session file onto the page and let her investigate. She reconstructs what happened in plain English, flags the risky moves — deploys, config and production changes, secrets — and traces each one back to the exact turn where it happened.

Image 2: CleanShot 2026-06-07 at 15.33.19@2x

She shows where the tokens went, which tools, subagents, skills, and MCP servers were used, and — only when a named, fixable pattern fires — what you could have done better, grounded in Anthropic’s and the community’s best practices. She _suggests, never asserts_, and stays silent when there’s nothing worth saying.

There’s also a built-in copilot: Ask Her. Ask _“why was this tool used?”_ and she answers from the trace, cites the turns, and opens the exact tool call. Drop one file for a session view; drop several to build a project view and hunt a question across many sessions at once.

Image 3: CleanShot 2026-06-07 at 15.34.50@2x

No third-party AI API is ever called. The model — Nemotron-Mini-4B-Instruct — runs on the Space’s own GPU via ZeroGPU. Your session is uploaded only to a private, auto-deleted namespace that belongs to your run, and nothing about it leaves the box.

The split that makes this trustworthy: the evaluation engine is purely deterministic. The model is used _only_ to write the English and propose softer suggestions. It never asserts a finding. The numbers don’t move when the model changes.

Image 4: CleanShot 2026-06-07 at 15.34.15@2x

One nice detail: Her doesn’t just list the CLI tools a session used — she identifies them. A database of top tools from Homebrew, npm, and PyPI ships with the Space, so most tools are named offline with a one-line blurb. When deploy tools, database clients, or dev servers are actually executed, Her flags that activity for the second look it deserves.

It grew over a weekend. It started as an operator’s view — a journey graph where every query is a node sized by cost, the heaviest one glowing — built for a friend.

Image 5: CleanShot 2026-06-07 at 15.16.31@2x

I showed it to another friend who wanted it simpler, so the graph grew an executive Report that’s now the default. Then the first friend asked why _their_ CLI tool didn’t show up — which is how the tool database was born.

Image 6: CleanShot 2026-06-07 at 15.17.45@2x

The frontend is a React app served straight off a Gradio server, with the deterministic engine doing the forensics and Nemotron handling the prose.

When Claude loses his mind, call Her. ;)

Try it here: Her on Hugging Face

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Her · हेर - Claude Code 会话分析工具 | AI HOT 精选 | traeai