How do I install the Mem Search skill?

Run npx skillmds@latest add djnsty23/mem-search in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

What does the Mem Search skill do?

Search persistent project memory across sessions — decisions, bugs, features, discoveries It is listed under Coding & Dev Tools on SkillMD.

Is Mem Search safe to use?

This skill has not completed SkillMD's automated safety review yet. Capability flags: reads secrets. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Mem Search?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Mem Search free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Mem Search?

djnsty23 (@djnsty23) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Mem Search by djnsty23 — Agent Skill

Name: Mem Search
Rating: 4.2 (5 reviews)
Author: djnsty23

File contents

Memory Search

Search the project's persistent memory database. Observations are captured automatically during sessions.

Commands

Say	Does
`mem search <query>`	Keyword search — auto-falls back to conceptual (semantic) search when exact matches are sparse
`mem why <query>` / `semantic`	Conceptual/fuzzy recall (TF-IDF token similarity + synonym expansion)
`mem recent`	Last 10 observations for this project
`mem decisions`	All architectural/design decisions
`mem bugs`	All bug fixes
`mem timeline <query>`	Session-level view with summaries
`mem sessions`	List all past sessions
`mem stats`	Memory database statistics

How It Works

Memory is stored in SQLite at ~/.claude/auto-dev-memory.db. Observations are captured automatically by the PostToolUse hook and classified by type:

decision — Architectural or design choices
bugfix — Bug fixes and patches
feature — New functionality added
refactor — Code restructuring
discovery — Investigations and findings
change — General modifications

Progressive Disclosure (Token-Efficient)

Start with mem search — returns titles + timestamps only (~50-100 tokens)
Then mem timeline — shows session context around matches (~500 tokens)
Then drill into specifics — full observation details only when needed

This 3-layer approach saves ~10x tokens vs dumping full context.

Implementation

Run queries via the memory-db CLI:

# Search — exact FTS5 first, auto-falls back to conceptual search when <3 exact hits
node "${CLAUDE_PLUGIN_ROOT}/scripts/memory-db.js" search "$(pwd)" "auth middleware"

# Conceptual / fuzzy recall (lexical TF-IDF ranker, no embeddings, offline)
node "${CLAUDE_PLUGIN_ROOT}/scripts/memory-db.js" semantic "$(pwd)" "why did we choose X"

# Recent observations
node "${CLAUDE_PLUGIN_ROOT}/scripts/memory-db.js" recent "$(pwd)" 10

# Decisions only
node "${CLAUDE_PLUGIN_ROOT}/scripts/memory-db.js" decisions "$(pwd)"

# Bug fixes only
node "${CLAUDE_PLUGIN_ROOT}/scripts/memory-db.js" bugs "$(pwd)"

# Session history
node "${CLAUDE_PLUGIN_ROOT}/scripts/memory-db.js" sessions "$(pwd)"

# Timeline search
node "${CLAUDE_PLUGIN_ROOT}/scripts/memory-db.js" timeline "$(pwd)" "database"

# Stats
node "${CLAUDE_PLUGIN_ROOT}/scripts/memory-db.js" stats "$(pwd)"

When to Use

Starting a new session and want context from past work
Remembering why a decision was made
Finding when/where a bug was fixed
Checking what was explored in previous sessions
Reviewing what's left to do (next_steps from last session)

Privacy

Content wrapped in <private>...</private> tags is automatically stripped before storage. Secrets, API keys, and sensitive data in private tags never reach the database.

Proving the run

Observable: the number of records searched, printed alongside the results.

"No memories match" is indistinguishable from "the database did not open". Before reporting an empty result, run a query you know should hit — a term from a memory written this week — and confirm it returns. Then report the count searched, so a zero is legible as a real absence rather than a silent failure.

---name: mem-searchdescription: Search persistent project memory across sessions — decisions, bugs, features, discoveries---# Memory SearchSearch the project's persistent memory database. Observations are captured automatically during sessions.## Commands| Say | Does ||-----|------|| `mem search <query>` | Keyword search — auto-falls back to conceptual (semantic) search when exact matches are sparse || `mem why <query>` / `semantic` | Conceptual/fuzzy recall (TF-IDF token similarity + synonym expansion) || `mem recent` | Last 10 observations for this project || `mem decisions` | All architectural/design decisions || `mem bugs` | All bug fixes || `mem timeline <query>` | Session-level view with summaries || `mem sessions` | List all past sessions || `mem stats` | Memory database statistics |## How It WorksMemory is stored in SQLite at `~/.claude/auto-dev-memory.db`. Observations are captured automatically by the PostToolUse hook and classified by type:- **decision** — Architectural or design choices- **bugfix** — Bug fixes and patches- **feature** — New functionality added- **refactor** — Code restructuring- **discovery** — Investigations and findings- **change** — General modifications## Progressive Disclosure (Token-Efficient)1. **Start with `mem search`** — returns titles + timestamps only (~50-100 tokens)2. **Then `mem timeline`** — shows session context around matches (~500 tokens)3. **Then drill into specifics** — full observation details only when neededThis 3-layer approach saves ~10x tokens vs dumping full context.## ImplementationRun queries via the memory-db CLI:```bash# Search — exact FTS5 first, auto-falls back to conceptual search when <3 exact hitsnode "${CLAUDE_PLUGIN_ROOT}/scripts/memory-db.js" search "$(pwd)" "auth middleware"# Conceptual / fuzzy recall (lexical TF-IDF ranker, no embeddings, offline)node "${CLAUDE_PLUGIN_ROOT}/scripts/memory-db.js" semantic "$(pwd)" "why did we choose X"# Recent observationsnode "${CLAUDE_PLUGIN_ROOT}/scripts/memory-db.js" recent "$(pwd)" 10# Decisions onlynode "${CLAUDE_PLUGIN_ROOT}/scripts/memory-db.js" decisions "$(pwd)"# Bug fixes onlynode "${CLAUDE_PLUGIN_ROOT}/scripts/memory-db.js" bugs "$(pwd)"# Session historynode "${CLAUDE_PLUGIN_ROOT}/scripts/memory-db.js" sessions "$(pwd)"# Timeline searchnode "${CLAUDE_PLUGIN_ROOT}/scripts/memory-db.js" timeline "$(pwd)" "database"# Statsnode "${CLAUDE_PLUGIN_ROOT}/scripts/memory-db.js" stats "$(pwd)"```## When to Use- Starting a new session and want context from past work- Remembering why a decision was made- Finding when/where a bug was fixed- Checking what was explored in previous sessions- Reviewing what's left to do (next_steps from last session)## PrivacyContent wrapped in `<private>...</private>` tags is automatically stripped before storage. Secrets, API keys, and sensitive data in private tags never reach the database.## Proving the run**Observable:** the number of records searched, printed alongside the results."No memories match" is indistinguishable from "the database did not open". Beforereporting an empty result, run a query you know should hit — a term from amemory written this week — and confirm it returns. Then report the countsearched, so a zero is legible as a real absence rather than a silent failure.

Frequently asked questions

Mem Search