Fixing Claude Export Conversations logo

Fixing Claude Export Conversations

CommunityPopular
daymade
fixing-claude-export-conversations

Fixes broken line wrapping in Claude Code exported conversation files (.txt), reconstructing tables, paragraphs, paths, and tool calls that were hard-wrapped at fixed column widths. Includes an automated validation suite (generic, file-agnostic checks). Triggers when the user has a Claude Code export file with broken formatting, mentions "fix export", "fix conversation", "exported conversation", "make export readable", references a file matching YYYY-MM-DD-HHMMSS-*.txt, or has a .txt file with broken tables, split paths, or mangled tool output from Claude Code.

Overview

Publisherdaymade
Repositoryclaude-code-skills
Skill namefixing-claude-export-conversations
Stars
1.4K
Forks
219
Bundled files
3
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by daymade on GitHub. Read the source before you install it.

Installation

Install the Fixing Claude Export Conversations AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/daymade/claude-code-skills.git /tmp/claude-code-skills
mkdir -p .claude/skills
cp -r /tmp/claude-code-skills/daymade-claude-code/claude-export-txt-better .claude/skills/fixing-claude-export-conversations
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Fixing Claude Export Conversations in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Fixing Claude Export Conversations on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Fixing Claude Export Conversations is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Fixing Claude Code Export Conversations

Reconstruct broken line wrapping in Claude Code exported .txt files.

Quick Start

bash
# Fix and show stats
uv run <skill-path>/scripts/fix-claude-export.py <export.txt> --stats

# Custom output
uv run <skill-path>/scripts/fix-claude-export.py <export.txt> -o fixed.txt

# Validate the result (53 automated checks)
uv run <skill-path>/scripts/validate-claude-export-fix.py <export.txt> fixed.txt

Replace <skill-path> with the resolved path to this skill's directory. Find it with:

bash
find ~/.claude -path "*/fixing-claude-export-conversations/scripts" -type d 2>/dev/null

Workflow

Copy this checklist and track progress:

- [ ] Step 1: Locate the exported .txt file
- [ ] Step 2: Run fix script with --stats
- [ ] Step 3: Run validation suite
- [ ] Step 4: Spot-check output (tables, CJK paragraphs, tool results)
- [ ] Step 5: Deliver fixed file to user

Step 1: Locate the file. Claude Code exports use the naming pattern YYYY-MM-DD-HHMMSS-<slug>.txt.

Step 2: Run the fix script.

bash
uv run <skill-path>/scripts/fix-claude-export.py <input.txt> -o <output.txt> --stats

Review the stats output — typical results: 20-25% line reduction, 80+ table borders fixed, 160+ table cells fixed.

Step 3: Run the validation suite.

bash
uv run <skill-path>/scripts/validate-claude-export-fix.py <input.txt> <output.txt>

All checks must pass. If any fail, investigate before delivering. Use --verbose for full details on passing checks too.

Step 4: Spot-check. Open the output and verify:

  • Tables have intact borders (box-drawing characters on single lines)
  • CJK/English mixed text has pangu spacing (Portal 都需要, not Portal都需要)
  • Tool result blocks () have complete content on joined lines
  • Diff output within tool results has each line number on its own line

Step 5: Deliver the fixed file to the user.

What Gets Fixed

The script handles 10 content types using a state-machine with next-line look-ahead:

  • User prompts ( prefix, dw=76 padding) — paragraph joins with pangu spacing
  • Claude responses ( prefix) — narrative, bullet, and numbered list joins
  • Claude paragraphs (2-space indent) — next-line look-ahead via _is_continuation_fragment
  • Tables — border reconstruction, cell re-padding with pipe-count tracking
  • Tool calls (● Bash( etc.) — path and argument reconstruction
  • Tool results ( prefix) — continuation joins including deeper-indented fragments
  • Plan text (5-space indent) — next-line look-ahead via _is_plan_continuation_fragment
  • Agent tree (├─/└─) — preserved structure
  • Separators (────, ---) — never joined
  • Tree connectors (standalone ) — preserved

Key Design Decisions

Next-line look-ahead (not dw thresholds): Instead of asking "was this line wrapped?" (fragile threshold), the script asks "does the next line look like a continuation?" by examining its content patterns — lowercase start, CJK ideograph start, opening bracket, hyphen/slash/underscore continuation.

Pangu spacing: Inserts spaces between ASCII alphanumeric characters and CJK ideographs at join boundaries. Also triggers for %, #, +, : adjacent to CJK.

Mid-token detection: Joins without space when boundaries indicate identifiers (BASE_ + URL), paths (documents + /05-team), or hyphenated names (ready + -together). Exception: -- prefix gets a space (run + --headed).

Safety

  • Never modifies the original file
  • Marker counts verified: , , , , must match input/output
  • Runaway join detection: warns if any line exceeds 500 display-width
  • Strict UTF-8 encoding — no silent fallbacks

Dependencies

Python 3.10+ via uv run — zero external packages (stdlib only: unicodedata, argparse, re, pathlib, dataclasses).

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Fixing Claude Export Conversations AI skill do?

Fixes broken line wrapping in Claude Code exported conversation files (.txt), reconstructing tables, paragraphs, paths, and tool calls that were hard-wrapped at fixed column widths. Includes an automated validation suite (generic, file-agnostic checks). Triggers when the user has a Claude Code export file with broken formatting, mentions "fix export", "fix conversation", "exported conversation", "make export readable", references a file matching YYYY-MM-DD-HHMMSS-*.txt, or has a .txt file with broken tables, split paths, or mangled tool output from Claude Code.

Why use Fixing Claude Export Conversations on TypingMind?

Because you install it once and use it with any model. Fixing Claude Export Conversations is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Fixing Claude Export Conversations in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/daymade/claude-code-skills/tree/main/daymade-claude-code/claude-export-txt-better. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Fixing Claude Export Conversations?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Fixing Claude Export Conversations?

As many as you like. As long as a model supports skills, you can use Fixing Claude Export Conversations with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Fixing Claude Export Conversations AI skill free?

Yes. It is published on GitHub by daymade under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇