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mem-search

From claude-mem
38.4K
Install
1
Install the plugin
$
npx claudepluginhub thedotmack/claude-mem --plugin claude-mem

Want just this skill?

Then install: npx claudepluginhub u/[userId]/[slug]

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.

Tool Access

This skill uses the workspace's default tool permissions.

Skill Content

Memory Search

Search past work across all sessions. Simple workflow: search -> filter -> fetch.

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?"

3-Layer Workflow (ALWAYS Follow)

NEVER fetch full details without filtering first. 10x token savings.

Step 1: Search - Get Index with IDs

Use the search MCP tool:

search(query="authentication", limit=20, project="my-project")

Returns: Table with IDs, timestamps, types, titles (~50-100 tokens/result)

| ID | Time | T | Title | Read |
|----|------|---|-------|------|
| #11131 | 3:48 PM | 🟣 | Added JWT authentication | ~75 |
| #10942 | 2:15 PM | 🔴 | Fixed auth token expiration | ~50 |

Parameters:

  • query (string) - Search term
  • limit (number) - Max results, default 20, max 100
  • project (string) - Project name filter
  • type (string, optional) - "observations", "sessions", or "prompts"
  • obs_type (string, optional) - Comma-separated: bugfix, feature, decision, discovery, change
  • dateStart (string, optional) - YYYY-MM-DD or epoch ms
  • dateEnd (string, optional) - YYYY-MM-DD or epoch ms
  • offset (number, optional) - Skip N results
  • orderBy (string, optional) - "date_desc" (default), "date_asc", "relevance"

Step 2: Timeline - Get Context Around Interesting Results

Use the timeline MCP tool:

timeline(anchor=11131, depth_before=3, depth_after=3, project="my-project")

Or find anchor automatically from query:

timeline(query="authentication", depth_before=3, depth_after=3, project="my-project")

Returns: depth_before + 1 + depth_after items in chronological order with observations, sessions, and prompts interleaved around the anchor.

Parameters:

  • anchor (number, optional) - Observation ID to center around
  • query (string, optional) - Find anchor automatically if anchor not provided
  • depth_before (number, optional) - Items before anchor, default 5, max 20
  • depth_after (number, optional) - Items after anchor, default 5, max 20
  • project (string) - Project name filter

Step 3: Fetch - Get Full Details ONLY for Filtered IDs

Review titles from Step 1 and context from Step 2. Pick relevant IDs. Discard the rest.

Use the get_observations MCP tool:

get_observations(ids=[11131, 10942])

ALWAYS use get_observations for 2+ observations - single request vs N requests.

Parameters:

  • ids (array of numbers, required) - Observation IDs to fetch
  • orderBy (string, optional) - "date_desc" (default), "date_asc"
  • limit (number, optional) - Max observations to return
  • project (string, optional) - Project name filter

Returns: Complete observation objects with title, subtitle, narrative, facts, concepts, files (~500-1000 tokens each)

Examples

Find recent bug fixes:

search(query="bug", type="observations", obs_type="bugfix", limit=20, project="my-project")

Find what happened last week:

search(type="observations", dateStart="2025-11-11", limit=20, project="my-project")

Understand context around a discovery:

timeline(anchor=11131, depth_before=5, depth_after=5, project="my-project")

Batch fetch details:

get_observations(ids=[11131, 10942, 10855], orderBy="date_desc")

Why This Workflow?

  • Search index: ~50-100 tokens per result
  • Full observation: ~500-1000 tokens each
  • Batch fetch: 1 HTTP request vs N individual requests
  • 10x token savings by filtering before fetching
Stats
Stars38412
Forks2777
Last CommitFeb 23, 2026

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