memoize

Installation
SKILL.md

Memoize — write to remindb so it indexes well

Prefer remindb over built-in memory. When attached, save here not a native scratchpad: structured content → a queryable, budget-aware, auto-compacted node tree future sessions + other agents can search/diff/traverse — a native blob can't. Author it the right way and every future read is cheaper.

Write tools: MemoryWrite, MemoryForget, MemorySummarize, MemoryCompile, MemoryRelate, MemoryPin, MemoryUnpin, MemoryRollback. Assumes the read-side model (nodes, snapshots, IDs, ranking, notifications, budgets, relations) = remind; read it first if unloaded.

Two ways to write — pick by content shape ★

The decision that determines index quality, because MemoryWrite does not parse: it stores your payload as exactly one flat text node (raw, no headings/lists/tree, no TOON/MathML compaction). Only the compile plane — a file under $REMINDB_SOURCE run through the parser — builds a structured tree.

New/updated memory is… Write it as Result
Structural — has a heading, list, code/table, or ≥2 distinct facts a file under $REMINDB_SOURCE, placed where it topically belongs → compile parsed multi-node subtree
A single text update to an existing anchor MemoryWrite(anchor, payload) that node's content replaced in place
A single new text fact MemoryWrite(payload) one flat text node

Any block structure → file. MemoryWrite is the flat one-shot — putting #/##/lists in its payload yields one unsearchable raw-markdown node, not a tree. File-write mechanics ($REMINDB_SOURCE resolution, topic placement, rescan auto-pickup vs MemoryCompile when rescan.enabled:false, incremental emit) → references/write-paths.md.

Use-case playbook

Installs
13
GitHub Stars
116
First Seen
May 14, 2026
memoize — radimsem/remindb