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Search conversation history and semantic memory to recall previous discussions, decisions, and context. Use when the user asks to "search memory", "what did we discuss", "remember when", "find previous conversation", "check history", or before starting work to recall prior decisions.
npx claude-code-templates@latest --skill ai-maestro/memory-searchSearch your conversation history using semantic, keyword, and symbol matching. Recall past decisions, discussions, and context across sessions. Part of the AI Maestro suite.
Requires AI Maestro running locally. Memory indexing uses CozoDB for vector search.
# Install memory tools
git clone https://github.com/23blocks-OS/ai-maestro-plugins.git
cd ai-maestro-plugins && ./install-memory-tools.sh
Before starting any task, search memory for relevant context:
Receive instruction -> Search memory -> Then proceed
| Command | Description |
|---|---|
memory-search.sh "<query>" | Hybrid search (recommended) |
memory-search.sh "<query>" --mode semantic | Find conceptually related |
memory-search.sh "<query>" --mode term | Exact text matching |
memory-search.sh "<query>" --mode symbol | Code symbol matching |
memory-search.sh "<query>" --role user | Only user messages |
memory-search.sh "<query>" --role assistant | Only assistant messages |
| Mode | Best For |
|---|---|
hybrid (default) | General search, most cases |
semantic | Related concepts, different wording |
term | Exact function/class names |
symbol | Code identifiers across contexts |
# User asks to continue previous work
memory-search.sh "authentication"
# Find a specific component discussion
memory-search.sh "PaymentService" --mode term
# Find related design discussions
memory-search.sh "error handling patterns" --mode semantic
# Find code symbol references
memory-search.sh "processPayment" --mode symbol
For complete context, pair with docs-search and graph-query:
memory-search.sh "feature" # What did we discuss?
docs-search.sh "feature" # What do docs say?
graph-describe.sh ComponentName # What is the structure?
This skill is part of the AI Maestro platform, which provides 6 skills for AI agent orchestration: messaging, memory, docs, graph, planning, and agent management.