Agent skill

Mem Search

Searches past coding sessions for observations, decisions, context.

Apache-2.0Auto-check: notesAgent Workflows

Install Mem Search

skills CLI

$ npx skills add softspark/ai-toolkit --skill mem-search -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install softspark/ai-toolkit mem-search --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/softspark/ai-toolkit.git skills-src && mkdir -p .claude/skills && cp -r skills-src/app/skills/mem-search .claude/skills/mem-search && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Paste into Claude Code

Install the "mem-search" agent skill from https://github.com/softspark/ai-toolkit/tree/main/app/skills/mem-search into .claude/skills/mem-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mem-search", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/softspark/ai-toolkit/tree/main/app/skills/mem-search

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add softspark/ai-toolkit --skill mem-search -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install softspark/ai-toolkit mem-search --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/softspark/ai-toolkit.git skills-src && mkdir -p .agents/skills && cp -r skills-src/app/skills/mem-search .agents/skills/mem-search && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "mem-search" agent skill from https://github.com/softspark/ai-toolkit/tree/main/app/skills/mem-search into .agents/skills/mem-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mem-search", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add softspark/ai-toolkit --skill mem-search -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install softspark/ai-toolkit mem-search --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/softspark/ai-toolkit.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/app/skills/mem-search .cursor/skills/mem-search && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "mem-search" agent skill from https://github.com/softspark/ai-toolkit/tree/main/app/skills/mem-search into .cursor/skills/mem-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mem-search", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/softspark/ai-toolkit.git --path app/skills/mem-search

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add softspark/ai-toolkit --skill mem-search -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install softspark/ai-toolkit mem-search --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/softspark/ai-toolkit.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/app/skills/mem-search .gemini/skills/mem-search && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "mem-search" agent skill from https://github.com/softspark/ai-toolkit/tree/main/app/skills/mem-search into .gemini/skills/mem-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mem-search", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install softspark/ai-toolkit mem-search

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add softspark/ai-toolkit --skill mem-search -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/softspark/ai-toolkit.git skills-src && mkdir -p .github/skills && cp -r skills-src/app/skills/mem-search .github/skills/mem-search && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "mem-search" agent skill from https://github.com/softspark/ai-toolkit/tree/main/app/skills/mem-search into .github/skills/mem-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mem-search", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add softspark/ai-toolkit --skill mem-search -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install softspark/ai-toolkit mem-search --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/softspark/ai-toolkit.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/app/skills/mem-search .opencode/skills/mem-search && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "mem-search" agent skill from https://github.com/softspark/ai-toolkit/tree/main/app/skills/mem-search into .opencode/skills/mem-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mem-search", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: mem-search
GitHub stars: 179
Token cost: ~1.2k tokens
SKILL.md length: 426 words
Files: 1
Skills in repo: 112
Repo updated: Oct 8, 2026
First seen: Oct 7, 2026
Licence: Apache-2.0

At a glance

Searches past coding sessions for observations, decisions, context.

Works in 5 steps: Parse the search query from $ARGUMENTS.… → Initialize the database if it does not… → Run the FTS5 search against the… → …
Agent Workflows work in your project
SKILL.md covers How It Works, Instructions, Query Tips and Example, plus 3 more sections
Calls python3, sqlite3 and bash

What it does

Mem Search is an agent skill from softspark/ai-toolkit. Searches past coding sessions for observations, decisions, context. Triggers: mem-search, recall session, past work, prior decisions, session history.

Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Agent Workflows. The repository describes itself as: Professional-grade AI coding toolkit: 94 skills, 44 agents, multi-platform (Claude, Cursor, Windsurf, Copilot, Gemini, Cline, Roo Code, Aider, Augment, Antigravity, Codex CLI… The licence is Apache-2.0.

When your agent uses it

Agent Workflows work in your project

Example prompts

“Use the mem-search skill to search past coding sessions for observations, decisions, context”
“/mem-search”

Requirements

Python 3
Pre-approved tools (allowed-tools): Bash, Read

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

Parse the search query from $ARGUMENTS. If empty, prompt the user for a query.
Initialize the database if it does not exist
Run the FTS5 search against the observations table
Progressive disclosure -- present results in two stages
If no results found, suggest

What it can do on your machine

Read from SKILL.md and the folder at commit e40ed87. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves these tools, so the agent can use them without asking each time:
- Bash
- Read
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
- python3
- sqlite3
- bash
- pg_dump
- git
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md. Its commands use git, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Mem Search loads about 1.2k tokens when it runs. Until then it costs about 40 tokens; SKILL.md has 426 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~40
When it runs · the whole SKILL.md, loaded when a task matches: ~1.2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
```
allowed-tools: Bash, Read
```

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from softspark/ai-toolkit at commit e40ed87, republished under its Apache-2.0 licence (© softspark). 426 words, ~1,203 tokens.

Download SKILL.mdSave it as .claude/skills/mem-search/SKILL.md (or your agent's skills folder).

name: mem-search
description: Searches past coding sessions for observations, decisions, context. Triggers: mem-search, recall session, past work, prior decisions, session history.
allowed-tools: Bash, Read
effort: medium
argument-hint: [search query]
user-invocable: true

Search Session Memory

Search the persistent memory database for past coding observations, decisions, and context.

$ARGUMENTS

How It Works

This skill queries the SQLite FTS5 full-text search index at ~/.softspark/ai-toolkit/memory.db to find relevant observations from past sessions.

Instructions

Parse the search query from $ARGUMENTS. If empty, prompt the user for a query.

Initialize the database if it does not exist:

bash

python3 "$HOME/.softspark/ai-toolkit/hooks/../plugins/memory-pack/scripts/init_db.py" 2>/dev/null || true

Run the FTS5 search against the observations table:

bash

sqlite3 ~/.softspark/ai-toolkit/memory.db "
  SELECT o.id, o.session_id, o.tool_name, o.content, o.created_at,
         s.project_dir, s.summary
  FROM observations_fts fts
  JOIN observations o ON o.id = fts.rowid
  LEFT JOIN sessions s ON s.session_id = o.session_id
  WHERE observations_fts MATCH '<query>'
  ORDER BY rank
  LIMIT 10;
"

Replace <query> with the user's search terms. Escape single quotes by doubling them.

Progressive disclosure -- present results in two stages:

Stage 1: Summary view (show first)

markdown

## Memory Search: "<query>"

Found N results across M sessions.

| # | Session | Project | Tool | Time | Preview |
|---|---------|---------|------|------|---------|
| 1 | abc123  | /path   | Edit | 2025-01-15 | First 80 chars... |

Stage 2: Detail view (on request) Show the full observation content, session summary, and related observations from the same session.

If no results found, suggest:
- Trying broader search terms
- Checking if memory-pack hooks are installed
- Running init-db.sh if the database is missing

Query Tips

Use simple keywords: mem-search database migration
FTS5 supports prefix matching: migrat* matches "migration", "migrate"
Boolean operators: database AND NOT test
Column filters: tool_name:Edit to search only Edit tool observations

Example

bash

/mem-search "postgres migration rollback"

Typical output:

## Memory Search: "postgres migration rollback"
Found 3 results across 2 sessions.

| # | Session | Project          | Tool | Time       | Preview                              |
|---|---------|------------------|------|------------|--------------------------------------|
| 1 | abc123  | magento2-os      | Edit | 2026-03-12 | Rolled back 0042_add_tax_col...      |
| 2 | def456  | magento2-b2b     | Bash | 2026-02-28 | pg_dump before schema migration...   |
| 3 | abc123  | magento2-os      | Read | 2026-03-12 | Reviewed migration safety checklist  |

Rules

MUST escape single quotes in queries by doubling (it''s) — SQL injection into the FTS5 call will break the query
NEVER return the raw database path — treat ~/.softspark/ai-toolkit/memory.db as internal
CRITICAL: if the database does not exist, initialize it silently and return zero results — do not fail the skill
MANDATORY: present Stage 1 (summary table) first; only expand to Stage 2 on follow-up

Show full SKILL.md (188 more words)Show less

Gotchas

FTS5 MATCH is picky: hyphens, slashes, and dots are parsed as operator separators and will reject queries like mem-search api/v1 with a cryptic malformed MATCH expression. Wrap multi-token phrases with double-quotes: "api/v1" or "mem-search".
Results are ordered by rank (FTS5 relevance), not by created_at. A stale but high-ranked match outranks a fresh but weak one — include the created_at column and consider ORDER BY rank, created_at DESC for time-sensitive queries.
The database path is static at ~/.softspark/ai-toolkit/memory.db. If the user runs from a container, ~ resolves to the container's home, not the host's — the observation list will look empty. Check the env var SOFTSPARK_HOME before assuming the DB is missing.
observations_fts is a separate virtual table; when observations are deleted directly (not via the SDK) the FTS index can drift. If counts between observations and observations_fts differ, rebuild with INSERT INTO observations_fts(observations_fts) VALUES('rebuild');.

When NOT to Use

To search the KB or documentation — use /research-mastery or smart_query()
To find a specific commit — use git log --grep or /git-mastery
To list agent tasks — use TaskList or /plan
When memory-pack hooks are not installed — direct the user to install them first

Files

Just SKILL.md in app/skills/mem-search of softspark/ai-toolkit.

Open the folder on GitHubat commit e40ed87

Compare with similar skills

Mem Search next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Mem Search compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Mem Search this skillsoftspark/ai-toolkit	179	—	~1.2k	Automated safety check: Notes	Apache-2.0	yesterday
MCP Server Builderanthropics/skills	180k	63 repos	~2.3k	Automated safety check: Pass	Apache-2.0	today
Hook Development for Claude Code Pluginsanthropics/claude-plugins-official	38k	10 repos	~4.1k	Automated safety check: Notes	Apache-2.0	today
Using Superpowersfarm-fe/farm	5.6k	35 repos	~1.4k	Automated safety check: Pass	MIT	17 days ago
Executing Plans Inlineobra/superpowers	297k	2 repos	~5.1k	Automated safety check: Pass	MIT	today
Skill CreatorAzure/azqr	795	89 repos	~8.2k	Automated safety check: Pass	Apache-2.0	today

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Questions about Mem Search

What does Mem Search do?

Searches past coding sessions for observations, decisions, context. Mem Search is an agent skill from softspark/ai-toolkit. Searches past coding sessions for observations, decisions, context.

When should I use Mem Search?

Mem Search fits situations like: agent Workflows work in your project.

How do I install Mem Search in Claude Code?

Run `npx skills add softspark/ai-toolkit --skill mem-search -a claude-code`. Or copy the skill folder (app/skills/mem-search in softspark/ai-toolkit) into .claude/skills/mem-search in your project. Claude Code loads it when a task matches its description.

How do I install Mem Search in Codex?

Run `npx skills add softspark/ai-toolkit --skill mem-search -a codex`. Or copy the skill folder (app/skills/mem-search in softspark/ai-toolkit) into .agents/skills/mem-search in your project. Codex loads it when a task matches its description.

Can I use Mem Search in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add softspark/ai-toolkit --skill mem-search -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/mem-search, .gemini/skills/mem-search, .github/skills/mem-search and .opencode/skills/mem-search in your project.

What does Mem Search need to run?

Going by SKILL.md and its folder, Mem Search needs the command-line tools its instructions call (python3, sqlite3, bash, pg_dump and git). Our summary lists: Python 3. Its frontmatter pre-approves these tools: Bash, Read.

Does Mem Search access the network?

SKILL.md contains no URLs. Its commands use git, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Mem Search safe to install?

Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Mem Search use?

Mem Search is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Mem Search use?

About 1.2k tokens (SKILL.md is roughly 4.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Mem Search?

Skills that share tags, products or a category with Mem Search: MCP Server Builder (anthropics/skills, 180k stars), Hook Development for Claude Code Plugins (anthropics/claude-plugins-official, 38k stars), Using Superpowers (farm-fe/farm, 5.6k stars) and Executing Plans Inline (obra/superpowers, 297k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Mem Search?

softspark (a GitHub user) maintains it in softspark/ai-toolkit, which has 179 GitHub stars. The repository holds 112 skills in this directory. The repository was last updated on October 8, 2026.

Source: softspark/ai-toolkit on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Mem Search

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

Search Session Memory

How It Works

Instructions

Query Tips

Example

Rules

Gotchas

When NOT to Use

Files

Compare with similar skills

Similar skills

More from softspark/ai-toolkit

Related

Questions about Mem Search