Agent-Skills.md

Agent Skills: banana-claude-codex-import

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UncategorizedID: treydong/banana-skills/banana-claude-codex-import

Repository

treydong/banana-skills
TreyDongLicense: MIT
141

Install this agent skill to your local

pnpm dlx add-skill https://github.com/TreyDong/banana-skills/tree/HEAD/skills/banana-claude-codex-import

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skills/banana-claude-codex-import/SKILL.md

Skill Metadata

Name
banana-claude-codex-import
Description
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banana-claude-codex-import

Import local Claude Code (~/.claude/) and Codex (~/.codex/) conversation history into OpenClaw's memory system, making past coding work queryable and part of long-term memory.

When to use this skill

Use this skill when the user:

  • Wants to import, migrate, or consolidate Claude Code or Codex sessions
  • Asks to "导入" or "migrate" past coding agent conversations
  • Wants to make past Claude Code / Codex work searchable in memory
  • Needs to rebuild memory from previous coding agent sessions
  • Mentions ~/.claude/ or ~/.codex/ session files
  • Is reviewing past work and wants to extract key decisions/patterns into memory

What this skill does

  1. Detect whether Claude Code and/or Codex data exists locally
  2. Preview with --dry-run to show session count, date range, and sample content
  3. Import all sessions to logs/message-archive-raw/
  4. Generate memory candidates for distillation into MEMORY.md

Workflow

Step 1: Dry-run first

Always run with --dry-run first to verify data coverage:

python3 ~/.openclaw/skills/banana-claude-codex-import/scripts/import_conversations.py --dry-run

Check:

  • Session count (aim for 50+ for Claude Code, 50+ for Codex)
  • Date range
  • Whether content looks real (not just noise/environment context)

If results look good, proceed.

Step 2: Full import

python3 ~/.openclaw/skills/banana-claude-codex-import/scripts/import_conversations.py

This writes:

  • Session archives → logs/message-archive-raw/{claude_code,codex}/
  • Memory draft → memory/YYYY-MM-DD_import_candidates.md

Step 3: Distill into MEMORY.md

Read memory/YYYY-MM-DD_import_candidates.md and extract high-value content into MEMORY.md:

## Claude Code / Codex 导入记忆（YYYY-MM）

> N sessions imported from `logs/message-archive-raw/`

### 技术决策
- [key decision 1]
- [key decision 2]

### 项目 / 主题
- [project 1]: [what was done]
- [project 2]: [what was done]

### 工具 & 工作流
- [tool/workflow pattern observed across sessions]

Source data

| Source | Path | Format | |--------|------|--------| | Claude Code sessions | ~/.claude/projects/*.jsonl | JSONL, user/assistant/tool_result entries | | Claude Code index | ~/.claude/history.jsonl | sessionId → metadata | | Codex sessions | ~/.codex/sessions/**/rollout-*.jsonl | JSONL, session_meta/response_item entries |

CLI options

--dry-run              # Preview only, no files written
--source both          # Import both Claude Code and Codex (default)
--source claude_code   # Claude Code only
--source codex         # Codex only
--since YYYY-MM-DD     # Only sessions on or after date

What makes a good memory distillation

After import, the most valuable things to capture in MEMORY.md:

  1. Technical decisions — architecture choices, tools selected/rejected, what failed
  2. Recurring workflows — patterns in how the user works with coding agents
  3. Project context — what each project is about, key milestones
  4. Personal preferences — working style, communication patterns, explicit preferences stated

Avoid: verbatim copying of conversations. Capture the distilled meaning.