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Search claude-mem's persistent cross-session memory database. Use when user asks "did we already solve this?", "how did we do X last time?", or needs work from previous sessions.

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SKILL.md

name mem-search
description Search claude-mem's persistent cross-session memory database. Use when user asks "did we already solve this?", "how did we do X last time?", or needs work from previous sessions.

Memory Search

Search past work across all sessions. Simple workflow: search → get IDs → fetch details by ID.

When to Use

Use when users ask about PREVIOUS sessions (not current conversation):

  • "Did we already fix this?"
  • "How did we solve X last time?"
  • "What happened last week?"

The Workflow

ALWAYS follow this exact flow:

  1. Search - Get an index of results with IDs
  2. Timeline (optional) - Get context around top results to understand what was happening
  3. Review - Look at titles/dates/context, pick relevant IDs
  4. Fetch - Get full details ONLY for those IDs

Step 1: Search Everything

curl "http://localhost:37777/api/search?query=authentication&format=index&limit=5"

Required parameters:

  • query - Search term
  • format=index - ALWAYS start with index (lightweight)
  • limit=5 - Start small (3-5 results)

Returns:

1. [feature] Added JWT authentication
   Date: 11/17/2025, 3:48:45 PM
   ID: 11131

2. [bugfix] Fixed auth token expiration
   Date: 11/16/2025, 2:15:22 PM
   ID: 10942

Step 2: Get Timeline Context (Optional)

When you need to understand "what was happening" around a result:

# Get timeline around an observation ID
curl "http://localhost:37777/api/timeline?anchor=11131&depth_before=3&depth_after=3"

# Or use query to find + get timeline in one step
curl "http://localhost:37777/api/timeline?query=authentication&depth_before=3&depth_after=3"

Returns exactly depth_before + 1 + depth_after items - observations, sessions, and prompts interleaved chronologically around the anchor.

When to use:

  • User asks "what was happening when..."
  • Need to understand sequence of events
  • Want broader context around a specific observation

Step 3: Pick IDs

Review the index results (and timeline if used). Identify which IDs are actually relevant. Discard the rest.

Step 4: Fetch by ID

For each relevant ID, fetch full details:

# Fetch observation
curl "http://localhost:37777/api/observation/11131"

# Fetch session
curl "http://localhost:37777/api/session/2005"

# Fetch prompt
curl "http://localhost:37777/api/prompt/5421"

ID formats:

  • Observations: Just the number (11131)
  • Sessions: Just the number (2005) from "S2005"
  • Prompts: Just the number (5421)

Search Parameters

Basic:

  • query - What to search for (required)
  • format - "index" or "full" (always use "index" first)
  • limit - How many results (default 5, max 100)

Filters (optional):

  • type - Filter to "observations", "sessions", or "prompts"
  • project - Filter by project name
  • dateStart - Start date (YYYY-MM-DD or epoch timestamp)
  • dateEnd - End date (YYYY-MM-DD or epoch timestamp)
  • obs_type - Filter observations by type (comma-separated): bugfix, feature, decision, discovery, change

Examples

Find recent bug fixes:

curl "http://localhost:37777/api/search?query=bug&type=observations&obs_type=bugfix&format=index&limit=5"

Find what happened last week:

curl "http://localhost:37777/api/search?query=&type=observations&dateStart=2025-11-11&format=index&limit=10"

Search everything:

curl "http://localhost:37777/api/search?query=database+migration&format=index&limit=5"

Why This Workflow?

Token efficiency:

  • Index format: ~50-100 tokens per result
  • Full format: ~500-1000 tokens per result
  • 10x difference - only fetch full when you know it's relevant

Clarity:

  • See everything first
  • Pick what matters
  • Get details only for what you need

Error Handling

If search fails, tell the user the worker isn't available and suggest:

pm2 list  # Check if worker is running

Remember: ALWAYS search with format=index first. ALWAYS fetch by ID for details. The IDs are there for a reason - USE THEM.