memory-recall

memory-recall is a Memory stores & recall skill for AI agents, published by zhangfengcdt in the memoir repository on GitHub. Skillspace rates memory-recall F (45/100) and the safety scan rated it risky; the rating is based on static analysis only.

Risky. This skill has patterns associated with unsafe behaviour. Read the source carefully before running it.

Recall facts from past sessions via memoir. STORE PATH: ALWAYS compute first via `STORE=$(bash "$CLAUDE_PLUGIN_ROOT/scripts/derive-store-path.sh")` (or `$MEMOIR_STORE`). Pass `-s "$STORE"` on every call — never rely on memoir's connected default (frequently stale). PROCEDURE (single-shot default): ONE `summarize --depth 3 -n default` → pick at most 5–7 keys → batch `get`. Only escalate to drill (batched `--keys`) if the depth-3 response shows `total_memories > 1000` AND the query is broad. Never call `summarize --depth 1` separately — `--depth 3` already returns count + full key listing. EXCLUDE `metrics.*` unless args contain `--include-metrics`. NEVER shell out to `memoir recall` (legacy LLM-bundled, slow, requires OPENAI_API_KEY). First reply line MUST be a mode marker `[mode=get|fast|drill|flat|blame|diff]`. DEFAULT ON: invoke for any question or task that may depend on past preferences, decisions, conventions, or knowledge — questions touching prior state, meta/overview asks,…

Grade

F

Quality

45 / 100

Safety

Risky

GitHub stars

594

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