GoodMemory

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GoodMemory is a memory layer for AI products and coding agents.

Release source: this source targets the 0.8.3 stable release. Registry commands require [email protected] to be published. The release workflow verifies npm latest and the already published GitHub assets against the locally prepared manifest; it does not rebuild or publish.

It gives chat apps, copilots, and agent hosts a durable user/project memory loop: write selected facts, retrieve the right context, inject it into the next turn, audit what happened, and delete it when it is wrong.

GoodMemory is not an LLM, agent framework, vector database, or generic RAG system. It is the product memory layer between your app or installed agent host and the model runtime.

What You Get

• Durable memory API: remember, recall, buildContext, feedback, forget, exportMemory, importMemory, and deleteAllMemory.
• Installed agent memory for Codex and Claude Code through goodmemory setup, managed hooks, installed Codex pre-action, goodmemory status, read-only MCP, and opt-in writeback.
• Public write customization with GoodMemoryConfig.remember, RememberProfile, rememberRules, RememberInput.annotations, and named extractor ids.
• Package exports for goodmemory, goodmemory/ai-sdk, goodmemory/host, and goodmemory/http through compiled dist artifacts and TypeScript declarations.
• Local-first storage: Bun gets durable SQLite by default; explicit Postgres, injected adapters, and embedding providers can be added when needed.
• Evaluation and release evidence paths for deterministic tests, live evals, provider-backed evals, package smoke tests, and quality gates.

OpenAI Build Week 2026

Pre-existing foundation. GoodMemory existed before OpenAI Build Week. The pre-event foundation already included the core memory API, local SQLite/Postgres storage, installed-host integration, and the local Inspector. The hackathon entry is the work added after the submission period opened on July 13, 2026, not the entire repository.

Added during Build Week. Dated commits completed and published v0.6.0, strengthened generalized retrieval and iterative-recall verification, added claim-source provenance coverage, hardened installed-host canaries and leakage audits, and expanded the controlled Codex coding-effect evaluation path. Review the pre-event-to-Build-Week diff and its dated commit history for the exact boundary.

How Codex and GPT-5.6 were used. Codex with GPT-5.6 was the primary implementation and verification environment: exploring the repository, implementing and reviewing changes, writing regression tests, reproducing installed-host behavior, and exercising the release and coding-effect evidence paths. GPT-5.6 also powers disclosed non-judge model calls in current evaluation