dsh-knowledge-sync

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Freeze every round of a DeepSeek Harness conversation into a knowledge-base document, and let later conversations find it.

A round ends, and what was asked, what was concluded, and which tools ran become one Markdown file. Nothing is sent to a model to make that happen. Later, an agent working in the same directory is told the base exists — two sentences, not the documents — and decides for itself whether to look.

What you get

Install

dsh plugin --profile web add dsh-knowledge-sync
dsh --profile web --dump-config   # shows a "# == dsh-knowledge-sync" layer
dsh web

Documents land in ./knowledge beside wherever you launched, or wherever DSH_KNOWLEDGE_ROOT points. Override anything in the profile's cordis.patch.yml:

- id: knowledge
  config:
    root: /srv/project/knowledge

What a document looks like

---
id: "abc12345-t1"
title: "Why is the build red?"
session: "abc12345-0000-4000-8000-000000000000"
turn: 1
created: "2026-08-18T10:00:00.000Z"
kind: "raw"
outcome: "completed"
cwd: "/srv/project"
tools: ["bash"]
---

# Why is the build red?

## Question

Why is the build red?

## Answer

The lockfile was stale — `pnpm install` had not been re-run after the
dependency bump.

## Tools

- `bash` — {"command":"pnpm install"}

Reasoning is left out on purpose: a document records the conclusion, not the working that reached it. A round that committed no answer is not written at all — an abandoned turn records that something was attempted, not something learned.

Three kinds of document

How recall works

The plugin does not paste the knowledge base into the conversation. A previous round is usually irrelevant to the current one, and injecting the lot would spend the context window on that irrelevance and invalidate the prompt prefix every time a round is written.

Instead an agent working in a directory with recorded rounds sees one short section:

Knowledge base — 12 documents from earlier conversation rounds for this workspace (/srv/project) are available. They are NOT included in this conversation.

Call knowledge_search when the task resembles work that may already have been done here — a recurring build failure, a decision that was already made, a file whose purpose was already established. Search reads the documents themselves, so a phrase from the conclusion will find its round. Then knowledge_read the ones worth reading in full. Prefer checking over repeating work, and prefer your own judgement over a stale document when the two disagree.

knowledge_search searches document bodies through the in-memory BM25 index — not just titles and tool names — and returns titles, kinds, tags, and a snippet of the match. Notes and distilled findings rank above raw transcripts, because a finding written down deliberately is worth more than a round that happened to record one. knowledge_search can also filter by kind, tag, and tool. knowledge_read returns one document in full, by id, and only for documents the same rule made visible.

A workspace with nothing recorded contributes no section at all. A pointer to an empty shelf teaches the model to stop believing the pointer.

Configuration

Each row is independent: drop knowledge-http in a composition with no web server, or knowledge-recall to record without offering recall, and the rest still works.

Install note. The package is a Cordis bundle: its cordis.patch.yml must stay in step with its build output. Rebuild (pnpm run build) after changing source so lib/ carries every module the patch references (the capture, note, recall, http, distill, policy, redact, search and settings entries), then add dsh-knowledge-sync to your profile's dsh.profile.bundles and restate in your profile's cordis.patch.yml any row you override. A patch row pointing at a not-yet-built lib/<module>.js will fail the profile boot.

Config is optional. The store registers a knowledge settings namespace so the page's Config tab is writable. If no settings service is mounted, nothing changes behavior: the rows' Config defaults stay authoritative and the tab reports that live settings are unavailable.

Development

The repository is self-contained — it develops against the published @deepseek-ai/* packages, the same versions a dsh installation ships:

pnpm install
pnpm run typecheck
pnpm run test
pnpm run build

Pin those devDependencies exactly, never by range: the registry's latest tag for several harness packages points at a much older release than the CLI installs, and a range resolves to that stale set.

The tests run the real thing — a real agent loop and a scripted model — because the shape of a session log is the one thing this plugin cannot guess at.

Known limitations

• Lexical search, not semantic. The in-memory BM25 index matches words (with CJK bigrams) — it cannot match a phrase it has never seen. Fitting in this data scale; the LLM seam has no embedding support yet.
• Recall is per directory. Sessions in a subdirectory of a recorded workspace do not see it, because the match is exact.
• No relation tracking yet. Documents can still contradict each other silently; the supersedes / staleness signals from the plan's third phase are not built.
• Distillation is opt-in. Off by default; enabling it costs one small model call per kept round.
• Documents are read-only on the page. The knowledge base is written by the conversations that produced it; a page that could rewrite history would make a document mean less than the round it froze. (Config is editable; documents are not.)

License

MIT