Xf

xf Knowledge Extraction

Core Insight: Your X archive is a goldmine. Sub-millisecond search makes iterative exploration practical. Mine your history before rebuilding context.

The Goldmine Principle

Your X archive contains:

• Public thoughts — Tweets capture your evolving thinking over years
• Private conversations — DMs hold detailed discussions, decisions, links shared
• AI interactions — Grok chats show what questions you asked and answers received
• Curated content — Likes reveal what resonated with you

The insight: Mining your X history surfaces forgotten context faster than rebuilding it.

THE EXACT PROMPT — Discovery Workflow

1. Bootstrap: Check health, get archive overview
   xf doctor && xf stats --format json | jq '{tweets, likes, dms, grok_messages}'

2. Search: Find content by topic (hybrid mode default = best)
   xf search "KEYWORD" --format json --limit 50

3. Filter by type: Narrow to specific content
   xf search "KEYWORD" --types dm --context --format json    # DMs w/ conversation
   xf search "KEYWORD" --types grok --format json            # AI Q&A

4. Follow hits: Get full context
   xf tweet <ID> --thread --format json                      # Tweet thread
   xf search "KEYWORD" --types dm --context --format json    # Full DM thread

5. Extract: Export for analysis
   xf search "topic" --format json --limit 1000 | jq '[.[] | {text, date: .created_at}]'

Why This Workflow Works

• Hybrid search first — Default mode combines keyword + semantic for best coverage
• --format json — Machine-readable output for piping to jq
• --context for DMs — Shows full conversation threads around matches
• Iterate fast — Sub-millisecond search enables exploration loops

Quick Reference

# Health + overview (ALWAYS first)
xf doctor && xf stats --format json

# Search modes (hybrid is default = best)
xf search "query" --format json                   # Hybrid (keyword + semantic)
xf search "exact phrase" --mode lexical           # Keyword only (BM25)
xf search "feeling stressed" --mode semantic      # Meaning-based

# Filter by content type
xf search "query" --types tweet --format json     # Your tweets
xf search "query" --types dm --context            # DMs with full conversation
xf search "query" --types like --format json      # Liked tweets
xf search "query" --types grok --format json      # Grok AI chats

# Date filtering
xf search "query" --since "2024-01" --until "2024-06" --format json
xf search "query" --since "last week" --format json

# Output control
xf search "query" --limit 100 --offset 50 --format json

When to Use What

Critical Rules

The Heuristics

jq Essentials

# Extract just text
| jq '.[].text'

# Text with dates
| jq '.[] | {text, date: .created_at}'

# Filter by engagement
| jq '[.[] | select(.favorite_count > 10)]'

# Count by year
| jq -r '.[].created_at[:4]' | sort | uniq -c

# DM conversation IDs
| jq '[.[].metadata.conversation_id] | unique'

# Find hashtags
| jq -r '.[].text' | grep -oE '#\w+' | sort | uniq -c | sort -rn

References

Scripts

Validation

# Quick health check
xf doctor

# Should show: all checks pass

If issues: run xf index --force to rebuild.