import-claude-session

name	import-claude-session
description	Import a claude.ai / Claude Desktop conversation as a resumable Claude Code session transcript.
when_to_use	Use when the user wants to bring a Claude Desktop or claude.ai chat into Claude Code, convert/export a conversation into a .jsonl session, or resume a web/desktop chat from the CLI.
argument-hint	[conversation name] [target project dir]
allowed-tools	["Bash"]
effort	medium

Import Claude Session

Pulls a conversation out of the Claude Desktop app (claude.ai) and writes it as a Claude Code .jsonl transcript so it appears in claude --resume for a chosen project directory.

The conversation content is not on disk. The desktop app only caches config locally; messages live on claude.ai's servers. The claude_session_to_cc.py script in this skill directory does all the deterministic work: it reads the desktop app's sessionKey cookie from the local Cookies store, decrypts it with the macOS Keychain key Claude Safe Storage, calls the claude.ai API to download the conversation, and converts it to the CC transcript format. Your job is to get the conversation name and target dir from the user, run the script, and report the result.

macOS only. The first run may surface a Keychain prompt the user must approve.

How the format maps

claude.ai stores one record per turn with a content array of blocks. Claude Code records one parentUuid-chained line per block. The script applies this mapping:

claude.ai block	Claude Code line
human message	user line, message.content = string
assistant thinking	assistant line, one thinking block
assistant text	assistant line, one text block
assistant tool_use	assistant line, one tool_use block
tool_result	user line with tool_result + toolUseResult

All blocks from one assistant turn share a generated message.id. The file lands in ~/.claude/projects/<cwd-with-slashes-as-dashes>/<session-id>.jsonl, so cwd determines which project's resume list shows it.

Steps

1. Get the conversation name and target dir

Ask the user which conversation (by title) and which project directory the session should belong to, unless they already said. The dir sets the cwd stamped in every line and the project folder the file lands in.

2. Find the conversation

Run: ${CLAUDE_SKILL_DIR}/claude_session_to_cc.py list

It prints [{uuid, name, updated_at}] as JSON. Confirm the exact title with the user if there's no clean match. If a Keychain prompt appears, tell the user to approve it.

3. Convert

Run: ${CLAUDE_SKILL_DIR}/claude_session_to_cc.py convert --name "<title>" --cwd "<project dir>"

Use --id <uuid> instead of --name if titles collide. The script prints {session_id, out_path, lines, source_name, cwd}.

4. Verify and report

Confirm the transcript is well-formed before claiming success:

python3 -c "import json; ls=[json.loads(l) for l in open('<out_path>')]; print(len(ls),'lines ok')"

Tell the user the out_path and how to open it: cd <cwd> && claude --resume, then pick the session (it shows the conversation's first prompt).

Rules

• Never claim the content is on disk. It is fetched from claude.ai every time; the local files only hold the auth cookie.
• The decrypted sessionKey is a live credential. Do not print it, echo it, or write it anywhere. The script never emits it.
• Stub fields are stubs. Token/usage counts are zeroed (claude.ai exposes no per-turn usage) and web_search results are flattened to title+URL lists. State this if the user asks about fidelity; do not present them as real.
• Attachments are folded into the human message text (pasted files inline, images as a [Attached image: ...] note). Binary image bytes are not downloaded.
• Don't fabricate a conversation. If list shows no match, report that and show the available titles rather than guessing a uuid.
• macOS only. If the Cookies db or Keychain item is missing, report it plainly; do not invent another extraction path.