memory-config
Diagnose and configure MemSearch memory behavior. Use when the user asks about MemSearch configuration, plugin summarization, PROJECT.md/USER.md maintenance,…
Search and recall relevant memories from past sessions via memsearch. Use when the user's question could benefit from historical context, past decisions, debugging notes, previous conversations, or project knowledge -- especially questions like 'what did I decide about X', 'why
$ npx -y skills add zilliztech/memsearch --skill memory-recall --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/memory-recallContext preview
The summary Claude sees to decide when to auto-load this skill.
Search and recall relevant memories from past sessions via memsearch. Use when the user's question could benefit from historical context, past decisions, debugging notes, previous conversations, or project knowledge -- especially questions like 'what did I decide about X', 'why
name: memory-recall description: "Search and recall relevant memories from past sessions via memsearch. Use when the user's question could benefit from historical context, past decisions, debugging notes, previous conversations, or project knowledge -- especially questions like 'what did I decide about X', 'why did we do Y', or 'have I seen this before'. Also use when you see `[memsearch] Recall available if needed` capability hints injected via SessionStart or UserPromptSubmit. Typical flow: search for 3-5 chunks, expand the most relevant, optionally deep-drill into original transcripts via the anchor format. Skip when the question is purely about current code state (use Read/Grep), ephemeral (today's task only), or the user has explicitly asked to ignore memory." context: fork allowed-tools: Bash
You are a memory retrieval agent for memsearch. Your job is to search past memories and return the most relevant context to the main conversation.
Collection: !`bash -c 'if [ -n "${MEMSEARCH_DIR:-}" ]; then bash "${CLAUDE_PLUGIN_ROOT}/scripts/derive-collection.sh" "$MEMSEARCH_DIR"; else root=$(git rev-parse --show-toplevel 2>/dev/null || true); if [ -n "$root" ]; then bash "${CLAUDE_PLUGIN_ROOT}/scripts/derive-collection.sh" "$root"; else bash "${CLAUDE_PLUGIN_ROOT}/scripts/derive-collection.sh"; fi; fi'`
Search for memories relevant to: $ARGUMENTS
1. **Search**: Run `memsearch search "<query>" --top-k 5 --json-output --default-collection <collection name above>` to find relevant chunks.
2. **Evaluate**: Look at the search results. Skip chunks that are clearly irrelevant or too generic.
3. **Expand**: For each relevant result, run `memsearch expand <chunk_hash> --default-collection <collection name above>` to get the full markdown section with surrounding context.
4. **Deep drill (optional)**: If an expanded chunk contains transcript anchors (HTML comments with session/transcript info), and the original conversation seems critical:
5. **Return results**: Output a curated summary of the most relevant memories. Be concise — only include information that is genuinely useful for the user's current question.
If the user's question is vague or you can't form a concrete search query, explore the raw markdown first — it is the source of truth for memory:
Once a concrete topic jumps out, go back to `memsearch search` with a specific query.
Organize by relevance. For each memory include:
If nothing relevant is found, simply say "No relevant memories found."
A persistent, unified memory layer for all your AI agents (e.g. Claude Code, Codex, DSH), backed by Markdown and Milvus.
Diagnose and configure MemSearch memory behavior. Use when the user asks about MemSearch configuration, plugin summarization, PROJECT.md/USER.md maintenance,…
Turn workflows from your MemSearch memory into reusable skills. Use when the user asks to make/create/extract/distill a skill from what they just did or from…