Local-first memory layer for AI agents with durable scoped storage, read-only recall, audit tools, and opt-in governed writeback.
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Inspect callable tools, capabilities, and parameters exposed to AI agents by GoodMemory.
Language: English | ็ฎไฝไธญๆ
GoodMemory is a memory layer for AI products and coding agents.
Release source: this is the immutable
0.7.5stable release source. Registry commands requiregoodmemory@0.7.5to be published. The release workflow verifies npmlatestand artifact integrity before creating the GitHub Release.
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.
remember, recall, buildContext, feedback, forget,
exportMemory, importMemory, and deleteAllMemory.goodmemory setup,
managed hooks, installed Codex pre-action, goodmemory status, read-only
MCP, and opt-in writeback.GoodMemoryConfig.remember,
RememberProfile, rememberRules, RememberInput.annotations, and named
extractor ids.goodmemory, goodmemory/ai-sdk, goodmemory/host,
and goodmemory/http through compiled dist artifacts and TypeScript
declarations.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. Install the published 0.7.5 registry baseline 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.
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.
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
score and disclosure fragments as self-attestation.
GoodMemory 0.7.5 has no current or versioned historical benchmark claim.
The retained v0.7.3 LoCoMo projection is not end-to-end runner evidence, so
it is an internal diagnostic. The v0.6.0
LoCoMo, BEAM, and MemoryAgentBench measurements and ImplicitMemBench are also
internal diagnostics under the same fail-closed boundary.
LongMemEval is withdrawn pending a clean rerun: the historical rules-only path
used answer annotations, and the later label-free path exposed raw
answer_* session IDs to retrieval and the reader. ImplicitMemBench's
retry-merged result remains internal evidence because it does not replace a
monolithic fresh run. HaluMem, MemGym, and MINTEval remain release evidence
rather than public benchmark claims.
No benchmark result is currently presented as measured on 0.7.5.
No end-to-end benchmark runner is currently allowlisted for versioned evidence.
No benchmark result currently qualifies as versioned historical evidence.
The retained v0.7.3 LoCoMo projection remains available in the repository for audit, but it is not shipped as a verified package artifact and cannot authorize a public or versioned claim. Old artifacts will not be retrofitted; a future producer and its verifier must be implemented together before promotion opens.
Where both are available, a row reports two tracks. The strict track is deterministic or judge-free โ a hard lower bound no LLM judge can inflate. The second track re-judges the same stored answers (not regenerated) under a benchmark-source or industry-standard prompt. Numerical comparability is claimed only when the pinned evaluator model and remaining benchmark configuration also match. Every per-protocol detail is recorded in the linked declarations.
The LongMemEval declaration is now paused_boundary, not historical evidence.
Its old numeric artifacts remain only to preserve the audit trail. They must
not be quoted as GoodMemory results until an opaque-session-id, label-free full
rerun replaces them; see the
withdrawal declaration.
The v0.6.0 BEAM, MemoryAgentBench, and LoCoMo measurements remain internal
diagnostics. They do not pass the empty end-to-end runner allowlist, so they are
not versioned historical evidence.
The ImplicitMemBench Full-300 stored-answer rescore uses the canonical zero-failure
run-phase61-full300-rerun-20260706-codex-current answers, then re-scores the
same stored answers with gpt-5.4 (sourceAnswersUnchanged: true). The judge is
cross-version but the same GPT family as the gpt-5.5 answer model, not a
cross-family judge. The recorded score is 0.691 (207.35/300) versus an
upstream-chat baseline of 0.400 (120/300), with 530 judge-required row
decisions across the baseline and GoodMemory arms; deterministic
structured_first_action rows are carried forward rather than judged. The
older same-model diagnostic score was 0.708 and is not the recorded result. The
freshest clean answer-regeneration drift check after recent code changes scored
0.6895 with executionFailures: 0; it shows current checkout drift, not a
replacement for the stored-answer comparability artifact. Its measured sources do
not independently expose both package version and commit at explicit JSON paths,
so the result is paused as an internal diagnostic and is not versioned historical
evidence. Dataset CC BY 4.0, fetched at eval time, never vendored.
LongMemEval's first current-recall assembly development slice is superseded:
although its reader context hid raw session IDs, the memory-builder boundary
still received gold-bearing session IDs and turn markers. A stricter v2
protocol now removes answers, question type, answer markers, and raw session
identities before memory construction. Its development slice must be rerun on
a clean commit before the still-sealed holdout can be opened; no LongMemEval
claim is restored. ImplicitMemBench's explicit retry-merged check reaches
0.6923666667 with zero failures, but it is not a replacement monolithic fresh
Full-300 run. Both therefore remain outside the current-claims table. The
underlying reports live under gitignored reports/ and are reproducible from
the recorded commands.
Use task-board/00-README.txt for execution order and docs/GoodMemory-Current-Status-and-Evidence.md for claim boundaries.
GoodMemory has three primary product entry points. They are not the only APIs:
lower-level surfaces such as goodmemory/host, custom stores, eval tooling, and
runtime helpers support these paths. They are the README-level ways to decide
how to start.
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