How it works

Two tools, one loop, on every code write:

• recall: before writing, the agent pulls your standards, ranked by relevance x burn count, trimmed to ~100 tokens.
• capture: when you correct it, the fix is compressed to one line and stored (or its burn count bumps).

Caveman rule format

[TAG] anti-pattern -> fix (xN)

Every rule is one terse line. The -> fix is mandatory, a rule without a concrete fix is just nagging and gets ignored. The xN burn count records how many times you have been corrected on it and drives ranking.

Part	Meaning
TAG	One of UI, COPY, CODE, COMMIT, SEC, REQ, PERF
anti-pattern	The habit to avoid
fix	The concrete thing to do instead
xN	Burn count: times you’ve been corrected on this rule. Higher burns rank higher in recall.

Examples:

[CODE]   invented APIs, guessed signatures -> verify against the docs first (x4)
[REQ]    gold-plating beyond the ask -> build only what's specced; ask first (x3)
[UI]     bespoke UI instead of the design system -> reuse tokens + components (x3)
[COPY]   "delve/seamless/robust" LLM slop -> plain, concrete language (x2)
[COMMIT] one giant, vague commit -> small, conventional: type(scope): msg (x2)
[SEC]    permissive defaults, missing authz -> deny by default, least privilege (x1)

What runs where

• Supermemory Local: the shared, on-machine store at http://localhost:6767. Holds the rich memories + local embeddings.
• Ranking is local: self-hosted vector search returns nothing (current release), so remindy lists via documents.list and ranks with a deterministic keyword scorer. Recall needs no LLM.
• Compression: an OpenAI-compatible model at capture time (BYOK). Unreachable? It falls back to a template so capture never blocks.

Two-layer data model

remindy stores a rich memory and injects a caveman projection derived from it.

{ "id": "…", "tag": "COPY", "antiPattern": "…", "fix": "…", "burns": 3, "createdAt": "…" }

• Match & dedup run on the rich memory.
• Only the one-line projection is injected into the agent.
• Projections can be regenerated from rich memories if compression improves.