session-logs

name	session-logs
description	Search and analyze your own session logs (older/parent conversations) using jq.
metadata	{"openclaw":{"emoji":"📜","requires":{"bins":["jq","rg"]}}}

session-logs

Search your complete conversation history stored in session JSONL files. Use this when a user references older/parent conversations or asks what was said before.

Trigger

Use this skill when the user asks about prior chats, parent conversations, or historical context that isn’t in memory files.

Location

Session logs live at: ~/.clawdbot/agents/<agentId>/sessions/ (use the agent=<id> value from the system prompt Runtime line).

• sessions.json - Index mapping session keys to session IDs
• <session-id>.jsonl - Full conversation transcript per session

Structure

Each .jsonl file contains messages with:

• type: "session" (metadata) or "message"
• timestamp: ISO timestamp
• message.role: "user", "assistant", or "toolResult"
• message.content[]: Text, thinking, or tool calls (filter type=="text" for human-readable content)
• message.usage.cost.total: Cost per response

Common Queries

List all sessions by date and size

for f in ~/.clawdbot/agents/<agentId>/sessions/*.jsonl; do
  date=$(head -1 "$f" | jq -r '.timestamp' | cut -dT -f1)
  size=$(ls -lh "$f" | awk '{print $5}')
  echo "$date $size $(basename $f)"
done | sort -r

Find sessions from a specific day

for f in ~/.clawdbot/agents/<agentId>/sessions/*.jsonl; do
  head -1 "$f" | jq -r '.timestamp' | grep -q "2026-01-06" && echo "$f"
done

Extract user messages from a session

jq -r 'select(.message.role == "user") | .message.content[]? | select(.type == "text") | .text' <session>.jsonl

Search for keyword in assistant responses

jq -r 'select(.message.role == "assistant") | .message.content[]? | select(.type == "text") | .text' <session>.jsonl | rg -i "keyword"

Get total cost for a session

jq -s '[.[] | .message.usage.cost.total // 0] | add' <session>.jsonl

Daily cost summary

for f in ~/.clawdbot/agents/<agentId>/sessions/*.jsonl; do
  date=$(head -1 "$f" | jq -r '.timestamp' | cut -dT -f1)
  cost=$(jq -s '[.[] | .message.usage.cost.total // 0] | add' "$f")
  echo "$date $cost"
done | awk '{a[$1]+=$2} END {for(d in a) print d, "$"a[d]}' | sort -r

Count messages and tokens in a session

jq -s '{
  messages: length,
  user: [.[] | select(.message.role == "user")] | length,
  assistant: [.[] | select(.message.role == "assistant")] | length,
  first: .[0].timestamp,
  last: .[-1].timestamp
}' <session>.jsonl

Tool usage breakdown

jq -r '.message.content[]? | select(.type == "toolCall") | .name' <session>.jsonl | sort | uniq -c | sort -rn

Search across ALL sessions for a phrase

rg -l "phrase" ~/.clawdbot/agents/<agentId>/sessions/*.jsonl

Tips

• Sessions are append-only JSONL (one JSON object per line)
• Large sessions can be several MB - use head/tail for sampling
• The sessions.json index maps chat providers (discord, whatsapp, etc.) to session IDs
• Deleted sessions have .deleted.<timestamp> suffix

Fast text-only hint (low noise)

jq -r 'select(.type=="message") | .message.content[]? | select(.type=="text") | .text' ~/.clawdbot/agents/<agentId>/sessions/<id>.jsonl | rg 'keyword'

Python Utilities

For more advanced extraction and analysis of Claude Code session logs, two Python scripts are provided:

extract_session.py

Extracts the conversation (user and assistant messages) from a Claude Code JSONL file.

python3 extract_session.py <jsonl_file>

Options:

• --thinking-full: Show full thinking text instead of truncation
• --tools-full: Show full tool call details
• --role <user|assistant>: Filter by role

Examples:

# Extract entire conversation
python3 extract_session.py session.jsonl

# Extract only assistant messages with full thinking
python3 extract_session.py session.jsonl --role assistant --thinking-full

# Extract with full tool call details
python3 extract_session.py session.jsonl --tools-full

extract_thinking.py

Extracts only thinking content from assistant messages.

python3 extract_thinking.py <jsonl_file>

Example:

python3 extract_thinking.py session.jsonl

These scripts handle the complex content structure (text, thinking, tool calls) and provide readable output. They are particularly useful for analyzing Claude Code's internal reasoning process.