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Conversation Search

conversation-search

Find and resume Claude Code conversations by searching topics or filtering by date. Returns session IDs and project paths for easy resumption via 'claude --resume'. Use when user asks "find that conversation about X", "what did we discuss", "what did we work on yesterday", "summarize today's work...

SKILL.md

Full skill instructions

Conversation Search

Find past conversations in your Claude Code history and get the commands to resume them.

MANDATORY FIRST STEP - CREATE TODO CHECKLIST

Before doing ANYTHING else, you MUST use the TodoWrite tool to create this exact checklist:

- Ensure cc-conversation-search tool is installed and upgraded
- Classify query type (temporal/​topic/​hybrid)
- Execute Level 1: focused search with cc-conversation-search
- Execute Level 2: broader search if Level 1 fails
- Execute Level 3: manual exploration if Level 1 and 2 fail
- Present results to user

CRITICAL CONSTRAINTS:

  • DO NOT use grep, find, cat, or any manual file operations on .jsonl files
  • DO NOT skip the todo creation step
  • DO NOT jump to Level 3 without attempting Levels 1 and 2
  • ONLY use cc-conversation-search commands for all search operations

Mark each todo as in_progress when starting it, completed when done.

Prerequisites & Auto-Installation

The skill requires the cc-conversation-search CLI tool (v0.4.0+ minimum).

First todo: Ensure tool is installed and upgraded

# Check if installed and upgrade
if command -v cc-conversation-search &> /​dev/​null; then
    uv tool upgrade cc-conversation-search 2>/​dev/​null || pip install --upgrade cc-conversation-search
    echo "Upgraded to: $(cc-conversation-search --version)"
else
    # Install if needed
    if command -v uv &> /​dev/​null; then
        uv tool install cc-conversation-search
    else
        pip install --user cc-conversation-search
        export PATH="$HOME/​.local/​bin:$PATH"
    fi
    # Initialize database
    cc-conversation-search init --days 7
fi

If installation fails, guide the user:

The conversation-search plugin requires the cc-conversation-search CLI tool.

Install it manually:
  uv tool install cc-conversation-search  (recommended)
  OR
  pip install --user cc-conversation-search

Then initialize:
  cc-conversation-search init

Do not proceed with search until installation is confirmed.

Query Type Classification

Second todo: Classify the user's query

Determine which type before executing search:

Type 1: Temporal Queries

User asks about time periods WITHOUT specific topics:

  • "What did we work on yesterday?"
  • "Summarize this week"
  • "Show today's conversations"

Action: Use list command with date filters

Type 2: Topic Queries

User asks about CONTENT/​TOPICS:

  • "Find that Redis conversation"
  • "Where did we discuss authentication?"
  • "Show me where we worked on the API"

Action: Use search "topic" command

Type 3: Hybrid Queries

User asks about TOPIC + TIME:

  • "Show me yesterday's authentication work"
  • "Find Redis discussions from last week"
  • "How many times did you say X in the past week?"

Action: Use search "topic" with date filters

Three-Level Search Workflow

Execute in order. Do not skip levels.

Level 1: Focused Search (ALWAYS START HERE)

Based on query classification:

For Topic or Hybrid queries:

cc-conversation-search search "search terms" --days 14 --json

For Temporal queries:

cc-conversation-search list --date yesterday --json  # or --days N, --since, --until

Parse the JSON output. If you find relevant matches → skip to Level 4 (present results).

Note: Search auto-indexes recent conversations for fresh data.

Level 2: Broader Search

Only if Level 1 found nothing useful.

For topic/​hybrid queries:

  • Remove time constraints: cc-conversation-search search "terms" --json
  • Try alternative keywords: "auth" vs "authentication"
  • Try broader terms: "database" vs "postgres"

For temporal queries:

  • Expand time range: --days 30 instead of --days 7

If matches found → skip to Level 4.

Level 3: Manual Exploration

Only if Levels 1 and 2 both failed.

  1. List conversations: cc-conversation-search list --days 30 --json
  2. Review conversation summaries in JSON
  3. For promising sessions: cc-conversation-search tree <SESSION_ID> --json
  4. Read message summaries to locate content

Level 4: Present Results

Format results for the user:

For found conversations:

**Session Details**
- **Session**: abc-123-session-id
- **Project**: /​home/​user/​projects/​myproject
- **Time**: 2025-11-13 22:50
- **Message**: def-456-message-uuid (if applicable)

**To Resume This Conversation**
```bash
cd /​home/​user/​projects/​myproject
claude --resume abc-123-session-id

For counting/​analysis queries:
- Parse JSON results
- Filter by message_type if needed (user vs assistant)
- Count matches
- Present clear answer with evidence

**If not found after all 3 levels:**
- "No matching conversations found after exhaustive search"
- Suggest: `cc-conversation-search index --days 90` to reindex older history
- "The conversation may not exist or may be older than indexed range"

## Command Reference

### Search (for topic and hybrid queries)
```bash
# With time scope
cc-conversation-search search "query" --days N --json

# Specific date
cc-conversation-search search "query" --date yesterday --json
cc-conversation-search search "query" --date 2025-11-13 --json

# Date range
cc-conversation-search search "query" --since 2025-11-10 --until 2025-11-13 --json

# All time
cc-conversation-search search "query" --json

Date filter options:

  • --days N: Last N days from now
  • --date DATE: Specific calendar day
  • --since DATE: From date onwards
  • --until DATE: Up to date (inclusive)
  • DATE formats: yyyy-mm-dd, yesterday, today
  • Cannot mix --days with --date/​--since/​--until

List (for temporal queries)

cc-conversation-search list --date yesterday --json
cc-conversation-search list --days 7 --json
cc-conversation-search list --since 2025-11-10 --until today --json

Context & Tree

cc-conversation-search context <UUID> --json
cc-conversation-search tree <SESSION_ID> --json

Always use --json for structured output.

Examples

Example 1: Topic query

User: "Find that conversation where we fixed the authentication bug"

Todo workflow:

  1. ✓ Tool installed/​upgraded
  2. ✓ Classify: TOPIC query
  3. ✓ Level 1: cc-conversation-search search "authentication bug" --days 14 --json
  4. If no results → Level 2: cc-conversation-search search "auth bug" --json
  5. Present results with resume commands

Example 2: Temporal query

User: "What did we work on yesterday?"

Todo workflow:

  1. ✓ Tool installed/​upgraded
  2. ✓ Classify: TEMPORAL query
  3. ✓ Level 1: cc-conversation-search list --date yesterday --json
  4. Parse conversations, group by project
  5. Present organized summary

Example 3: Hybrid query

User: "Show me yesterday's authentication work"

Todo workflow:

  1. ✓ Tool installed/​upgraded
  2. ✓ Classify: HYBRID query (topic + time)
  3. ✓ Level 1: cc-conversation-search search "authentication" --date yesterday --json
  4. Present matching sessions

Example 4: Counting/​analysis query

User: "How many times did you say 'absolutely right' in the past week?"

Todo workflow:

  1. ✓ Tool installed/​upgraded
  2. ✓ Classify: HYBRID query (phrase + time)
  3. ✓ Level 1: cc-conversation-search search "absolutely right" --days 7 --json
  4. Parse JSON, filter message_type == "assistant", count results
  5. Present count with context snippets

Error Handling

Tool not installed:

  • Guide user through installation (see Prerequisites section)
  • Do not proceed until confirmed

Database not found:

  • User must run: cc-conversation-search init
  • Creates ~/​.conversation-search/​index.db

Empty results:

  • Follow Level 1 → 2 → 3 progression
  • Do not give up after Level 1
  • Only report "not found" after Level 3 fails

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