Chat History

Chat History Search

Search through previous AI chat conversations stored locally by Cursor IDE and Claude Code.

Context Management Strategy

IMPORTANT: Chat histories can be massive. Never load full conversations into context unnecessarily.

Two-Stage Approach:

1. Search → Returns IDs + metadata + small excerpts (lightweight)
2. Extract → Load only what's needed from specific conversations

Native Tools vs Bash: For Claude Code JSONL files, prefer native tools when possible:

Bash is still useful for: pipes, parallel ops, complex jq transforms.

Main Agent vs Subagent:

Subagent Prompt Template (when appropriate):

Search my chat history for conversations about {topic}.
Find relevant conversations, extract key solutions/code, and summarize.
Return: conversation IDs, brief summary, relevant code snippets.
Do not return raw data - only summarized findings.

Detect the Tool

# Detect which exists (cross-platform)
# macOS
ls "$HOME/Library/Application Support/Cursor/User/globalStorage/state.vscdb" 2>/dev/null && echo "Cursor (macOS)"
# Linux
ls "$HOME/.config/Cursor/User/globalStorage/state.vscdb" 2>/dev/null && echo "Cursor (Linux)"
# Claude Code (same on macOS/Linux)
ls ~/.claude/projects/ 2>/dev/null && echo "Claude Code"

Cursor IDE

Stage 1: Search (Lightweight)

Returns IDs + metadata only. Never returns full conversation content.

List Recent (IDs + Size)

SELECT
  SUBSTR(key, 14) as id,
  LENGTH(value) as size,
  json_extract(value, '$.name') as title
FROM cursorDiskKV
WHERE key LIKE 'composerData:%'
ORDER BY ROWID DESC LIMIT 10;

Search by Keyword (IDs + Excerpt)

SELECT
  SUBSTR(key, 14) as id,
  LENGTH(value) as size,
  SUBSTR(value, MAX(1, INSTR(value, 'keyword') - 50), 150) as excerpt
FROM cursorDiskKV
WHERE key LIKE 'composerData:%'
  AND value LIKE '%keyword%'
ORDER BY ROWID DESC LIMIT 10;

Search Multiple Keywords (AND)

SELECT SUBSTR(key, 14) as id, LENGTH(value) as size
FROM cursorDiskKV
WHERE key LIKE 'composerData:%'
  AND value LIKE '%keyword1%'
  AND value LIKE '%keyword2%'
ORDER BY ROWID DESC LIMIT 10;

Find by File Path

SELECT SUBSTR(key, 14) as id, LENGTH(value) as size, json_extract(value, '$.name') as title
FROM cursorDiskKV
WHERE key LIKE 'composerData:%'
  AND value LIKE '%src/components/Button%'
ORDER BY ROWID DESC LIMIT 10;

Find with Code Blocks

SELECT SUBSTR(key, 14) as id, LENGTH(value) as size
FROM cursorDiskKV
WHERE key LIKE 'composerData:%'
  AND value LIKE '%"suggestedCodeBlocks":%'
  AND value LIKE '%"code":%'
ORDER BY ROWID DESC LIMIT 10;

Stage 2: Extract (On-Demand)

After finding relevant IDs, extract only what's needed.

Get Summary/Title Only

SELECT
  json_extract(value, '$.name') as title,
  json_extract(value, '$.latestConversationSummary.summary.summary') as ai_summary,
  json_extract(value, '$.composerId') as id
FROM cursorDiskKV
WHERE key = 'composerData:{id}';

Get Excerpt Around Match

SELECT SUBSTR(value, MAX(1, INSTR(value, 'keyword') - 200), 500) as excerpt
FROM cursorDiskKV
WHERE key = 'composerData:{id}';

Get Message Count

SELECT json_array_length(json_extract(value, '$.conversation')) as message_count
FROM cursorDiskKV
WHERE key = 'composerData:{id}';

Get First N Messages (Legacy Format)

SELECT json_extract(value, '$.conversation[0].text') as msg1,
       json_extract(value, '$.conversation[1].text') as msg2,
       json_extract(value, '$.conversation[2].text') as msg3
FROM cursorDiskKV
WHERE key = 'composerData:{id}';

Get Full Conversation (Use Sparingly!)

-- WARNING: Loads entire JSON blob - can be 100KB-500KB per conversation
-- Prefer json_extract() for specific fields when possible
SELECT value FROM cursorDiskKV WHERE key = 'composerData:{id}';

Prefer partial extraction:

-- Instead of full load, extract only what you need:
SELECT
  json_extract(value, '$.name') as title,
  json_extract(value, '$.conversation[0].text') as first_msg,
  json_extract(value, '$.conversation[1].text') as first_reply
FROM cursorDiskKV WHERE key = 'composerData:{id}';

Advanced SQLite Functions

For complex queries, use SQLite's full power:

JSON Functions

-- Extract nested field
json_extract(value, '$.conversation[0].text')

-- Array length
json_array_length(json_extract(value, '$.conversation'))

-- Check if field exists
json_type(value, '$.name') IS NOT NULL

String Functions

-- Extract excerpt around match (MAX prevents negative index)
SUBSTR(value, MAX(1, INSTR(value, 'keyword') - 100), 300)

-- Get position of match
INSTR(value, 'search_term')

-- Case-insensitive search
value LIKE '%keyword%' COLLATE NOCASE

Filtering & Ranking

-- By size (substantial conversations)
ORDER BY LENGTH(value) DESC

-- By recency (chronological)
ORDER BY ROWID DESC

-- Combined score
ORDER BY (LENGTH(value) / 1000) + (ROWID / 1000000) DESC

Aggregations

-- Count total
SELECT COUNT(*) FROM cursorDiskKV WHERE key LIKE 'composerData:%';

-- Count by criteria
SELECT COUNT(*) FROM cursorDiskKV
WHERE key LIKE 'composerData:%' AND value LIKE '%typescript%';

Claude Code

Stage 1: Search (Lightweight)

Returns file paths only, not content. Tip: Filter by project first for speed.

Find by Keyword (Files Only)

# All projects (slower ~2s)
grep -rl "keyword" ~/.claude/projects/ --include="*.jsonl" | head -10

# Specific project (faster)
grep -rl "keyword" ~/.claude/projects/-Users-me-myproject/ --include="*.jsonl"

Find Multiple Keywords (AND)

grep -rl "keyword1" ~/.claude/projects/ --include="*.jsonl" | xargs grep -l "keyword2" | head -10

Find by File Path Discussed

grep -rl "src/components/Button" ~/.claude/projects/ --include="*.jsonl" | head -10

Find by Project

# List all projects with conversations
ls ~/.claude/projects/

# List conversations for specific project
# Path encoding: /Users/me/my-project → -Users-me-my-project
ls ~/.claude/projects/-Users-me-my-project/

# All conversations for a project
find ~/.claude/projects/-Users-me-my-project/ -name "*.jsonl" -type f

# Last N conversations for a project (by modification time)
ls -lt ~/.claude/projects/-Users-me-my-project/*.jsonl | head -2

# Search within a project only (fast)
grep -rl "keyword" ~/.claude/projects/-Users-me-my-project/ --include="*.jsonl"

Get Tool Operations on a File

# Which tools were used on a specific file and how many times?
FILE=~/.claude/projects/{project}/{conversation}.jsonl
TARGET="src/components/Button.tsx"
grep "$TARGET" "$FILE" | jq -r '
  .message.content[]? | select(.type=="tool_use") |
  "\(.name): \(.input.file_path // "other")"
' 2>/dev/null | sort | uniq -c | sort -rn

Output example: 15 Edit: /path/to/file.tsx, 9 Read: /path/to/file.tsx

Recent Conversations

find ~/.claude/projects/ -name "*.jsonl" -mtime -7 -type f | head -20

List with Metadata

find ~/.claude/projects/ -name "*.jsonl" -type f -exec ls -lh {} + | sort -k6,7 -r | head -20

Stage 2: Extract (On-Demand)

Get Line Count (Message Estimate)

wc -l < ~/.claude/projects/{project}/{file}.jsonl

Get Matching Lines Only (Not Full File)

grep "keyword" ~/.claude/projects/{project}/{file}.jsonl

Get Match with Context

grep -B1 -A1 "keyword" ~/.claude/projects/{project}/{file}.jsonl

Get First/Last N Lines

# First 10 messages
head -10 ~/.claude/projects/{project}/{file}.jsonl

# Last 10 messages
tail -10 ~/.claude/projects/{project}/{file}.jsonl

# Messages 20-30
sed -n '20,30p' ~/.claude/projects/{project}/{file}.jsonl

Extract User Messages Only (Streaming)

# All user messages (streams line-by-line, doesn't load full file)
grep '"type":"user"' ~/.claude/projects/{project}/{file}.jsonl | jq -r '.message.content'

# First 5 user messages only
grep -m 5 '"type":"user"' ~/.claude/projects/{project}/{file}.jsonl | jq -r '.message.content'

Extract Assistant Messages Only (Streaming)

# First 3 assistant text responses
grep -m 3 '"type":"assistant"' ~/.claude/projects/{project}/{file}.jsonl | jq -r '.message.content[] | select(.type=="text") | .text'

Get Summary Stats (Fast - Parallel)

FILE=~/.claude/projects/{project}/{file}.jsonl
echo "total: $(wc -l < "$FILE")" &
echo "user: $(grep -c '"type":"user"' "$FILE")" &
echo "assistant: $(grep -c '"type":"assistant"' "$FILE")" &
wait

Note: Parallel greps (300ms) beat jq -s (235ms). For files >50MB, streaming is essential to avoid memory issues.

Useful Queries

Find by Error Message

# "How did I fix this error before?"
grep -rl "Cannot find module" ~/.claude/projects/ --include="*.jsonl" | head -5

Extract Bash Commands Run

# "What commands did I run?"
grep '"Bash"' {file}.jsonl | jq -r '.message.content[]? | select(.name=="Bash") | .input.command' | head -10

Extract Web Searches

# "What did I research?"
grep "WebSearch" {file}.jsonl | jq -r '.message.content[]? | select(.name=="WebSearch") | .input.query'

Find Failed Operations

grep '"is_error":true' {file}.jsonl | jq -r '.content[0:200]'

Activity Timeline (This Week)

# "What projects did I work on?"
find ~/.claude/projects/ -name "*.jsonl" -mtime -7 -type f | \
  sed 's|.*/projects/||; s|/.*||' | sort | uniq -c | sort -rn | head -10

Find Subagent Tasks

# "What complex tasks did I delegate?"
grep '"Task"' {file}.jsonl | jq -r '.message.content[]? | select(.name=="Task") | .input.prompt[0:100]'

Advanced jq Patterns

For complex extraction, use jq's full power:

Filter by Message Type

jq 'select(.type=="assistant")' file.jsonl

Extract Specific Fields

jq '{type, content: .message.content[0:200]}' file.jsonl

Find Messages Mentioning File

jq 'select(.message.content | contains("Button.tsx"))' file.jsonl

Extract Tool Calls

jq 'select(.type=="tool_use") | {tool: .name, input: .input}' file.jsonl

Truncate Long Content

jq '.message.content = .message.content[0:300]' file.jsonl

Aggregate with slurp (small files only)

# WARNING: jq -s loads entire file into memory - avoid on files >10MB
cat file.jsonl | jq -s 'group_by(.type) | map({type: .[0].type, count: length})'

Performance Guide

Fast Operations

Slow Operations (Avoid)

Claude Code: Project Path Encoding

Filter by project for 10x faster searches:

/Users/me/my-project → ~/.claude/projects/-Users-me-my-project/

Best Practices

Do

• Always start with Stage 1 (search) to find relevant IDs
• Use LIMIT and head -N to cap results
• Filter by project path before keyword search
• Use grep -c for counts instead of jq -s | length
• Extract excerpts around matches, not full content

Don't

• Use jq -s on files >10MB
• Run grep -rl across all projects without | head
• Load full conversations into context unnecessarily
• Skip the search stage and guess conversation IDs

Size Thresholds

• Small (<100KB): Safe to load full
• Medium (100KB-1MB): Load excerpts or specific messages
• Large (>1MB): Only load matching lines/fields

Quick Reference

Resources

references/

• cursor-schema.md - Cursor database schema and JSON format
• claude-code-schema.md - Claude Code JSONL format documentation