hjqcan/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 goodmemory@0.8.3 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
profiles; public-claim paths either use deterministic scoring or keep the judge
independent from the answer model.
**Run and verify.** After publication, install 0.8.3 from the registry and inspect
its local memory surface:
Verify the repository from source with bun install --frozen-lockfile,
bun test, and bun run typecheck. See the
Devpost submission and
public demo video.
**Claim boundary:** the submission demonstrates durable cross-session memory,
governed writeback, recall evidence, and inspection/deletion infrastructure. It
does not claim that GoodMemory has already proven an improvement in Codex
coding outcomes; that paired hidden-test evaluation remains an active,
fail-closed evidence track.
Start Here: Codex Or Claude Code
No account or hosted service is required. GoodMemory stores memory locally in
SQLite by default, wires lifecycle hooks plus read-only MCP inspection, and
keeps durable writeback opt-in. Verify the installation with
goodmemory status.
Using another MCP client or integrating an application? Choose an integration
path.
Benchmark Results
GoodMemory separates current-production claims, versioned historical evidence,
and internal research. A number may enter the current-claims table only after
gate:public-benchmark-claim --strict validates a committed declaration for
the current package version: complete coverage, executionFailures: 0, a
no-memory baseline, deterministic scoring or an independent judge, verified
dataset source and license, and a reproducible run (commit + command + package
version). No end-to-end benchmark runner is allowlisted today, so promotion is
unavailable for both current and historical rows. Stored-answer rescores and
legacy presentation projections cannot open that boundary or supply README