Agent Archive

Persistent conversation export and replay for AI agents system for Claude Code, Caveman, OpenClaw, Hermes, MCP agents, and multi-agent workflows. Use when user asks to export, save, archive, persist, snapshot, serialize, or backup conversations/chat sessions.

Persistent conversation export and replay for AI agents.

Supports:

• Markdown export
• JSONL export
• RAG-ready chunking
• Tool call persistence
• Session metadata
• TOC generation
• Long conversation optimization
• Replay-friendly structure
• Auto-summary
• Multi-format export

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Export Modes

Mode	Purpose
compact	Human readable
full	Full forensic session export
rag	Vector DB / RAG ingestion
replay	Agent replay & observability
jsonl	AI training datasets

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Default Save Paths

text

.claude/agent-archives/
.claude/agent-archives/jsonl/
.claude/agent-archives/replay/

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Export Metadata

Always include:

yaml

session_id:
conversation_id:
exported_at:
model:
agent:
cwd:
message_count:
tool_calls:
export_mode:

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Long Conversation Rules

If conversation > 30 turns:

• generate TOC
• add anchors
• collapse large tool outputs
• summarize repetitive sections

If conversation > 100 turns:

• split into chunks
• generate session summary
• create chunk index

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Tool Call Rules

Preserve:

• tool name
• arguments
• tool result
• timing
• errors
• retry count

Example:

json

{
  "tool": "Write",
  "success": true,
  "latency_ms": 230
}

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RAG Export Rules

When using rag mode:

• insert chunk markers
• preserve semantic boundaries
• preserve code fences
• keep markdown headings stable

Chunk format:

markdown

<!-- chunk:start id=12 -->
...
<!-- chunk:end -->

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Replay Mode

Replay mode should preserve chronological execution:

1. user input
2. assistant reasoning summary
3. tool call
4. tool result
5. assistant response

This mode is designed for:

• debugging
• benchmarking
• observability
• workflow replay