open-preset-harness

Project memory for multi-role AI agents — one knowledge base, every preset reads.

English | 中文

Agents forget between sessions. Teams don't.
open-preset-harness adds a project-scoped organizational memory layer on top of DeepSeek Harness: any role (preset) can contribute experience; any role can recall it when needed.

Why this exists

DeepSeek Harness separates preset (who the agent is — tools, persona, prompts) from session log (what happened in one conversation). That split is right for engineering — but team knowledge lives at the project level, not inside a single preset or session.

Without shared memory:

• A security review preset rediscovers the same auth pitfalls every sprint
• A new contributor preset repeats questions answered three months ago
• Product decisions vanish when the PM's session ends
• Token spend grows because every role rebuilds context from scratch

open-preset-harness makes project experience compound over time — like a team wiki that agents actually use, wired into the harness session log.

What it is (and is not)

Relationship to DeepSeek Harness

DeepSeek Harness (upstream, MIT)
        │
        ├── preset  = role shell (tools + persona)
        ├── session = episodic log (one conversation)
        │
        └── open-preset-harness (this project)
                └── project memory = shared team experience (cross-preset, cross-session)

• Upstream: DeepSeek Harness — plugin-based agent harness on Cordis
• Our approach: Prefer plugins + conventions over a hard fork; track upstream releases
• License: MIT — we preserve upstream copyright in NOTICE
• Naming: This is an independent community project, not an official DeepSeek product

We upstream-friendly fixes when possible; project-memory features live here until (if ever) they graduate upstream.

See docs/architecture.md and docs/phase-0-memory-api.md.

Core concepts

┌─────────────────────────────────────────────────────────┐
│              Project Memory (shared)                       │
│   index · domains · decisions · distilled learnings      │
└────────────────────────▲────────────────────────────────┘
                         │ write (distill) / read (recall)
     ┌───────────────────┼───────────────────┐
     │                   │                   │
  Preset A            Preset B            Preset C
  (any role)          (any role)          (any role)
     │                   │                   │
  Session 1           Session 2           Session N
  (episodic log)      (episodic log)      (episodic log)

1. Preset — role/capability shell (unchanged Harness semantics)
2. Session log — full history of one conversation (unchanged)
3. Project memory — stable, distilled, searchable facts the whole team reuses

Design rules

• One memory pool per project — all presets read (governance controls write)
• Organize by domain/topic, not by preset id (e.g. security, api, onboarding)
• Index + recall on demand — don't dump the whole library every turn
• Model-visible ⟺ logged — Harness invariant; memory enters via inject/tools/session events

Default layout:

<projectRoot>/.dsh/memory/
├── index.md
├── domains/
│   ├── engineering.md
│   ├── product.md
│   └── …
└── decisions/
    └── YYYY-MM-slug.md

Scenarios

More in docs/scenarios.md.

Status

🚧 Early experiment — testing product–market fit in CN + EN communities.

Star ⭐ if you want updates. Issues and scenario PRs are the best way to help us validate the idea.

Roadmap

Phase 0 — Prove the story (weeks 1–4)

• [x] Memory API draft (tools + frontmatter schema)
• [ ] Harness plugin: inject index.md on blank session; recall / remember tools
• [ ] Demo repo + 3-minute screen recording
• [ ] Bilingual README + scenarios doc

Phase 1 — Team-ready basics (months 1–3)

• [ ] Domain taxonomy helpers + conflict / supersede rules
• [ ] Turn-end or manual distill hook (session → memory, opt-in)
• [ ] Git-friendly diff workflow for memory changes
• [ ] Integration notes with Harness compaction + session-reference

Phase 2 — Scale retrieval (months 3–6)

• [ ] Semantic search (optional local embed index)
• [ ] Memory budget / ranking / citation in tool results
• [ ] CLI: oph memory status, oph memory search

Phase 3 — Enterprise-shaped (demand-driven)

• [ ] Write ACL by domain
• [ ] Audit export, approval before publish
• [ ] Hosted sync (optional SaaS — not required for OSS core)

Priorities shift with your Issues — tell us your scenario.

Quick start

Plugin implementation: packages/tool-project-memory · tests passing

1. Harness integration — link plugin into local Harness
2. Dual-preset demo — standard writes, code reads
3. Open a Scenario Issue — tag en-scenario or cn-scenario

chmod +x scripts/link-harness.sh
./scripts/link-harness.sh /path/to/deepseek-harness-master

Contributing

See CONTRIBUTING.md.

High-impact contributions right now:

1. Add a scenario to docs/scenarios.md
2. Review docs/phase-0-memory-api.md
3. Chinese + English doc fixes

Community

• Issues — bugs, ideas, scenario requests
• Discussions — enable when repo is public
• Tag Issues with [cn-scenario] or [en-scenario] to help us track market signals

License

MIT — see LICENSE and NOTICE.
DeepSeek Harness is © DeepSeek; modifications © contributors.