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dsh-ai-memory

rasyidmmz/dsh-ai-memory

Memory bridge between DeepSeek Harness and ai-memory: runs ai-memory's finalize-session when a DSH session ends, so the observations it already captured become searchable wiki pages. Skips subagents, queues concurrent session ends, and sweeps sessions abandoned by a forced restart. Requires a separately installed ai-memory server with its DSH lifecycle hooks wired by hand — ai-memory’s own install-hooks does not support DSH; this plugin only finalizes what capture has already recorded.

Installation

dsh plugin --profile web add github:rasyidmmz/dsh-ai-memory

README

dsh-ai-memory

Memory bridge between DeepSeek Harness and ai-memory.

ai-memory shares one memory across 20+ coding agents: Claude Code, Codex, Cursor, Gemini CLI, OpenCode, and more all read and write the same wiki. DSH could only ever read it. This plugin makes DSH a full writer too.


What this is not

Read this first, because it decides whether this package is for you.

  • It is not ai-memory. ai-memory is a separate project by a different author. This plugin does not contain it, does not bundle it, and does not replace it.
  • It is not a fork of ai-memory. There is no shared code and no git relationship. ai-memory is written in Rust; this plugin is a single ~800-line JavaScript file that calls the ai-memory command-line program you install yourself. See Credits.
  • It is not affiliated with, endorsed by, or supported by ai-memory's author. It is an independent third-party integration.
  • It does not capture anything. It only finalizes sessions that ai-memory has already captured. Capture comes from DSH hook wiring that you install separately — see Prerequisites.

Credits

The memory engine this plugin drives is entirely the work of others:

akitaonrails/ai-memory — MIT licensed. One Rust binary that captures agent sessions through lifecycle hooks, consolidates them into a searchable Markdown wiki, and serves that memory to 20+ harnesses over MCP and HTTP.

No ai-memory code is included here. This repository contains zero lines taken from that project. It is a DSH-side adapter that shells out to the ai-memory binary, nothing more. If this plugin is useful to you, the credit belongs upstream — please star their repository.

Memory between harnesses

This is the point of the plugin, so it is worth stating precisely.

ai-memory is built on the idea that memory should follow you, not your editor. Quit Claude Code mid-task, open Codex in the same directory, and the next agent picks up a real handoff. That works because every harness writes into one shared store, and session-end consolidation turns the raw record into readable wiki pages the next agent can search.

DSH was the odd one out. ai-memory's consolidation is triggered by a session end event, and DSH never fires one — its session-terminating path exits through a signal that emits no disposal event at all. So DSH sessions landed in ai-memory as raw observations and stopped there:

Claude Code session ends ──► consolidated ──► wiki page ──► readable by every harness
DSH session ends         ──► raw observations only ──► invisible to every harness

DSH could search the memory other agents wrote, but nothing DSH did ever became memory the others could read. One-way, in the wrong direction.

This plugin closes that loop by firing the finalize step DSH never fires. With it installed:

DSH session ends ──► this plugin ──► ai-memory finalize-session ──► wiki page
                                                                      │
              Claude Code, Codex, Cursor, Gemini CLI, … ◄────────────┘

A DSH session becomes a page that Claude Code can retrieve, that a teammate's Codex can search, that shows up in the next agent's handoff brief. DSH stops being a read-only consumer of the shared memory and becomes a peer writer in it.

That is the whole value: not a new memory system, but one harness joining an existing one properly.

Prerequisites

Two things must already work. The plugin will not do either of them for you.

1. A running ai-memory server with capture wired into DSH.

Install ai-memory from upstream, then wire DSH's lifecycle hooks so events are captured. ai-memory's own install-hooks command does not support DSH (--agent dsh is rejected), so the hook file is written by hand. A working example is in docs/hooks-dsh.json.

Verify capture independently before blaming this plugin:

ai-memory status          # sessions and observations should be increasing
ai-memory doctor          # inside your project directory

2. The ai-memory CLI on the same machine.

That is all. It resolves its own data directory and server URL, so the default configuration needs no settings at all.

If the server is not running, this plugin logs a clear warning at startup and does nothing else. Capture failing is a separate problem with a separate cause.

Install

dsh plugin --profile web add dsh-ai-memory

From GitHub instead of npm:

dsh plugin --profile web add github:rasyidmmz/dsh-ai-memory

Restart DSH afterwards. The loader imports plugin code without a cache-buster, so an edited or newly added plugin is not picked up until the process restarts.

Confirm it loaded by searching the harness log for ai-memory:

[ai-memory] active v1.0.0 -- fast path session/disposed (zero idle cost) + ...
[ai-memory] preflight: ai-memory v2.4.0 | data_dir=... | server=127.0.0.1:49374

The preflight line is the fastest way to confirm the plugin found the same ai-memory your hooks are writing to.

Configuration

Optional. The defaults are correct for a standard ai-memory install, and the plugin behaves identically with no config: block at all.

- insert:
    - id: ai-memory
      name: dsh-ai-memory
      config:
        exePath: /usr/local/bin/ai-memory   # default: platform standard location
        dataDir: /home/me/.local/share/ai-memory  # default: let the CLI decide
        agentKind: claude-code              # default: claude-code
        sweep: true                         # default: true
        preflight: true                     # default: true
        timeoutMs: 120000                   # default: 120000
KeyDefaultMeaning
exePathWindows: %LOCALAPPDATA%\Programs\ai-memory\ai-memory.exe; elsewhere: ai-memory from PATHPath to the ai-memory executable.
dataDirunsetai-memory data directory. Leave unset unless you use a non-standard location; the CLI then resolves its own, which is what the hooks use.
agentKindclaude-codeThe agent kind recorded in ai-memory's store. See the note below — this is not a free choice.
sweeptrueThe abandoned-session safety net. Set false to disable it entirely.
preflighttrueLog one line at startup naming the ai-memory version, data directory, and server it found.
timeoutMs120000Per-finalize-session timeout.

Why agentKind should stay claude-code

ai-memory recognises a fixed set of agent kinds — claude-code, codex, cursor, open-code, opencode2, pi, omp, zero, kiro-cli, pool, zcode — and rejects anything else outright. There is no dsh kind.

DSH reaches ai-memory through the Claude Code hook bridge, so every captured DSH session is stored as claude-code. That is simply what the store contains, and finalize-session must be told to look there. Passing anything else — including the CLI's own default, which is codex — will match no session ever.

How it works

Two paths, deliberately asymmetric.

Fast path — an event, costing nothing while idle

When a session closes cleanly, DSH fires session/disposed. The plugin listens, derives the session's stored UUID, and calls ai-memory finalize-session.

  • Idle cost: zero. No timer, no query, no process started.
  • Reaction: immediate, not waiting for a scheduled sweep.

It uses session/disposed rather than the two events that fire alongside it because it is the only one carrying the full session object, so the working directory is read directly instead of being cached or guessed.

Safety net — the tiered sweeper

DSH terminates through SIGTERM, and SIGTERM fires no disposal event at all. A session open at that moment is never finalized: it stays open forever with no page. This is not hypothetical — one session with 459 observations was left behind that way.

So a sweeper exists that depends on no event: it reads ai-memory's store directly and finalizes sessions that are provably dead. Its schedule is dense at first and then eases off — 25s, 1 min, 3 min, 10 min, then every 30 min — because the only case an event misses is a session abandoned by a restart, which happens right when DSH starts.

Getting this wrong is worse than not doing it: finalizing a live session produces a page from half its content, and that page is never updated again. So four guards must all pass:

  1. the session is not in this process's live-session list;
  2. its last observation is more than 2 minutes old;
  3. its UUID is version 5 — main sessions only, never subagents;
  4. at most 10 sessions per sweep.

Guard 2 covers a second DSH window: that is a separate process, so its session is invisible here, and without the delay it would be closed mid-write.

Guard 3 has a useful side effect worth knowing if you run DSH alongside real Claude Code sessions in one repository: ai-memory stores those as version-4 UUIDs, so they can never be selected by this sweeper.

Set sweep: false to turn the whole net off; the fast path is unaffected.

The seven traps this solves

Each of these broke an earlier version, and each fix is load-bearing. They are worth listing because they are the reason a naive "just call finalize-session" plugin does not work.

  1. The session id is not a raw UUID. DSH ids look like session-<uuid> and ai-memory stores them as a derived UUID v5. Passing the raw string is rejected: invalid uuid: invalid character: found 's' at 1. Child agents use a bare UUID and must be passed as is — two id shapes, two treatments.
  2. The working directory must be explicit. The shell service defaults to the DSH process's own directory, not the session's repository, so scope resolves to the wrong project.
  3. The project name is not always the folder's basename. Hooks write it lowercased; the CLI derives it with original casing. Repositories without an .ai-memory.toml marker only match after a lowercase retry.
  4. No 2>&1. DSH runs commands with stderr unredirected, and collapsing it inside the command fails there, exiting non-zero having done nothing.
  5. Subagent detection must read the session header, not the registry. The agent registry deletes an entry before announcing its disposal, so a registry lookup is always empty — including for the main session. An earlier version used it as a filter and therefore skipped every agent, doing nothing at all while logging no error.
  6. Concurrent session ends must queue, not drop. Closing DSH with two sessions open fires two disposal events back to back; a naive running guard silently discards the second.
  7. SIGTERM fires nothing — hence the sweeper above.

Troubleshooting

All output is prefixed [ai-memory]. Search the harness log for it.

Log lineMeaningAction
active v1.0.0 ...Plugin loaded—
preflight: ai-memory vX | data_dir=...Found the serverConfirm the data directory matches your hooks
WARNING: ai-memory executable not foundWrong exePathSet exePath in config
preflight: the ai-memory server did not answerServer not runningStart ai-memory
session ... -> page createdWorking—
session ... -> no open session matchedAlready finalized, or never capturedCheck ai-memory status; if observations are not rising, the hooks are the problem, not this plugin
session ... FAILEDThe CLI returned an errorThe message tail is included
sweeper could not read the storeai-memory's schema changedThe fast path keeps working; only the safety net is down
sweeper: no abandoned sessionsNormal, most sweeps—

If nothing appears at all, the plugin is not loaded — check the profile's cordis.patch.yml and restart DSH.

Note on finalize-session and consolidation. This plugin calls finalize-session, which is a client of the running server. It does not invoke an LLM and does not write wiki pages itself; the server does that. If pages are not appearing, check the server's own logs.

Compatibility

  • DSH: developed and tested against DSH Desktop 0.9.1 (harness 0.1.5-rc.2), Node 24.
  • ai-memory: developed and tested against 2.4.0. The finalize-session flags used here were verified present in that release.
  • Platforms: Windows is the tested platform. Linux and macOS command construction is implemented and exercised, but not run end-to-end by the author — treat those as untested.
  • No dependencies. No dependencies, no peerDependencies, so there is no build step and no allowBuilds approval on install.
  • No tools, no UI. The plugin registers no model tools and draws no interface. It only listens and shells out.

If ai-memory changes

The plugin reads ai-memory's SQLite store directly in one place, the sweeper, and only to find abandoned sessions. If a future ai-memory release changes that schema, the sweeper logs an error and stops; the fast path is untouched because it uses no SQL at all. Set sweep: false to silence it entirely in that case.

License

MIT — see LICENSE. This license covers this plugin only. ai-memory is separately licensed (also MIT) by its own author.

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