memory-recall

You are performing memory retrieval for memsearch. Search past memories and return the most relevant context to the current conversation.

Project Collection

Determine the collection name by running:

bash -c 'if [ -n "${MEMSEARCH_DIR:-}" ]; then bash __INSTALL_DIR__/scripts/derive-collection.sh "$MEMSEARCH_DIR"; else root=$(git rev-parse --show-toplevel 2>/dev/null || true); if [ -n "$root" ]; then bash __INSTALL_DIR__/scripts/derive-collection.sh "$root"; else bash __INSTALL_DIR__/scripts/derive-collection.sh; fi; fi'

Steps

1. Search: Run memsearch search "<query>" --top-k 5 --json-output --collection <collection name from above> to find relevant chunks.

   • If memsearch is not found, try uvx memsearch instead.
   • Choose a search query that captures the core intent of the user's question.

2. Evaluate: Look at the search results. Skip chunks that are clearly irrelevant or too generic.

3. Expand: For each relevant result, get the full context using one of these methods:

   • Primary: Run memsearch expand <chunk_hash> --collection <collection name from above> to get the full markdown section.
   • Fallback (if expand fails with a lock/permission error due to sandbox): Read the source file directly. The search results include source (file path) and start_line/end_line — use cat <source_file> or read the relevant line range to get the full context. This avoids the Milvus lock file issue.

4. Deep drill (optional): If an expanded chunk contains transcript anchors (HTML comments with session/rollout info), and the original conversation seems critical:

   • Run bash __INSTALL_DIR__/scripts/parse-rollout.sh <rollout_path> to retrieve the original conversation turns.
   • If the anchor format is unfamiliar (e.g. transcript: + turn:, db: instead of rollout:), try reading the referenced file directly to explore its structure and locate the relevant conversation by the session or turn identifiers in the anchor.

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.

When unsure what to search

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:

• MDIR="${MEMSEARCH_DIR:-$(git rev-parse --show-toplevel 2>/dev/null || pwd)/.memsearch}"; ls -t "$MDIR/memory/" | head -10 — recent daily logs
• MDIR="${MEMSEARCH_DIR:-$(git rev-parse --show-toplevel 2>/dev/null || pwd)/.memsearch}"; grep -h "^## " "$MDIR/memory/"*.md | sort -u | tail -40 — session headings across all days
• MDIR="${MEMSEARCH_DIR:-$(git rev-parse --show-toplevel 2>/dev/null || pwd)/.memsearch}"; cat "$MDIR/memory/<YYYY-MM-DD>.md" — read a specific day

Once a concrete topic jumps out, go back to memsearch search with a specific query.

Output Format

Organize by relevance. For each memory include:

• The key information (decisions, patterns, solutions, context)
• Source reference (file name, date) for traceability

If nothing relevant is found, simply say "No relevant memories found."