DSH Marketplace

engramory

tinqiao-oss/engramory

The Engramory curated-memory discipline as an installable plugin ([npm: dsh-engramory](https://www.npmjs.com/package/dsh-engramory)): a deterministic 200-line / 25 KB cap on the `MEMORY.md` index via `ctx.tools.guard()` — growth denied, a shrinking rewrite always passes — plus the protocol registered as a runtime skill. The store is plain markdown, one file per fact, shared with Claude Code, Codex, Kiro, and OpenClaw.

19112PythonMITSource

Install

Add engramory to DeepSeek Harness

via GitHub · GitHub source

Installing from GitHub runs the project's build script, which pnpm blocks until you allowlist it — run the command once and pnpm prints the exact key to add under `allowBuilds` in ~/.dsh/profiles/web/pnpm-workspace.yaml.

What happened when we ran it

Installed cleanly when we ran it

Every command here is run in a throwaway container against a clean profile, and the result is whatever the harness recorded — not a guess from the source. Last run 11d ago.

Show it in your README

install verified — dshmarketplace

For maintainers: the badge serves this listing's latest sandbox verdict, so a re-run updates it on its own — and it links readers to the full result here.

Due diligence

Before you install engramory

  • Source of record: tinqiao-oss/engramory — present in the community registry that DSH's own plugin market installs from.
  • Licensed under MIT.
  • Detected: terminal surface, requires credentials. Read the source before granting these.
  • A listing here is not a security review. Plugins run with your agent's permissions.

The AI take

What it is — This DeepSeek Harness plugin provides a deterministic capping protocol for the MEMORY.md index.

Who it is for — It is suitable when managing Markdown fact storage in DeepSeek Harness. Users performing writes via shell commands or external editors do not need it, since the index capping does not cover those paths.

Watch out — Installation requires providing an API key or token. Sandbox testing passed in a fresh profile and the plugin was registered. No obvious issues found.

The verdict — I would install it because it denies growth past the index cap for matched edit tools.

Generated by grok-4.6, and a starting point rather than a verdict. Where it says a plugin installs or does not, that is from a real run in a clean profile — everything else is read off the repository. Trust the source over this.

What engramory does

Small fact tiles pass through an index gate that blocks growth and allows compacted memory through.

engramory is a DeepSeek Harness plugin that applies a curated, file-based memory protocol to an agent’s local markdown store. It keeps one MEMORY.md index alongside small, human-readable files containing individual facts, with no database, embeddings or server. The protocol is registered as a runtime skill and loaded as standing rules through CLAUDE.md, AGENTS.md or the host’s rules file.

The index is checked through ctx.tools.guard() by a PreToolUse hook for direct Edit, Write and MultiEdit operations. Growth is denied when MEMORY.md would exceed 200 lines or 25 KB; a rewrite that reduces its size is allowed. The discipline also asks the model to deduplicate before writing, update rather than duplicate, remove incorrect facts, and avoid storing information already covered by git, CLAUDE.md or the code. tools/engramory_doctor.py provides a validator.

This suits small-scale, local memory that people can read, edit and diff, particularly where a loaded index is preferable to a database-backed search layer. It is the wrong choice when writes must be globally enforced across shell, MCP, external-editor or sync-client paths: those bypass the hook, and the curation rules remain model-followed. The store assumes one serialised writer. The catalogue flags a terminal surface and credential requirements; the README does not specify which credentials are needed.

engramory documentation

How it behaves

Engramory uses plain markdown as its source of truth: one file per fact plus an always-loaded MEMORY.md index. The live store remains git-ignored. The protocol uses four role-based types: user, feedback, project and reference. feedback is procedural memory and requires Why: and How to apply: lines. Its curation contract covers deduplication before writing, updating instead of duplicating, deleting incorrect facts and excluding information already recorded in git, CLAUDE.md or source code.

The index is intended to stay within both limits below; whichever limit is reached first triggers the cap behaviour.

Limit Behaviour
150 lines / 20 KB Warning threshold
200 lines / 25 KB Compact or ask before writing

Guard and validator

The hard backstop is a PreToolUse hook using ctx.tools.guard(). It checks direct Edit, Write and MultiEdit operations affecting MEMORY.md. A change that would grow the index beyond either cap is denied. A shrinking or compaction rewrite is allowed.

The repository also provides tools/engramory_doctor.py, described as a validator for checking the memory store. The excerpt does not specify its command-line arguments or output format.

Requirements

Engramory is designed for local, file-based memory and does not require a database, embeddings or a server. Its rules are loaded through CLAUDE.md, AGENTS.md or the host’s equivalent rules file. The README describes the project as experimental, version 0.8.0, and assumes a single writer with serialised writes.

Known limits

The hook is not a global write guard. Bash, PowerShell, background Monitor commands, MCP file tools, external editors and sync clients can bypass it. The curation protocol is therefore best-effort and model-followed rather than guaranteed for every task. It is not intended as a mandatory cross-agent memory layer.

Written from the project's own documentation and kept in sync with it. Where the two disagree, the source is authoritative — read the README on GitHub

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