dsh-plugin-meta-memory

Structured long-term memory system for DeepSeek Harness.

What it does

Teaches the agent how to organize memories using a structured system:

• Units: Work categories named verb-modifier-noun.unit
• Records: Each memory has a brief (quick scan) and full (detailed) version
• Index: Self-maintained global storyline
• Auto-injection: Relevant briefs are injected into context automatically

Install

dsh plugin --profile your-profile add dsh-plugin-meta-memory

How it works

Memory structure

.meta-memory/
├── index.md
└── units/
    ├── debug-auth-module.unit/
    │   ├── 0.token-refresh-fail.brief.md
    │   └── 0.token-refresh-fail.full.md
    └── read-deeplearning-paper.unit/
        ├── 0.transformer-attention.brief.md
        └── 0.transformer-attention.full.md

Brief format (injected into context)

# token-refresh-fail
JWT token refresh returns 401 due to timestamp offset calculation error.

Full format (loaded on demand)

# token-refresh-fail

## Context
Auth module was failing on token refresh after 1 hour.

## Finding
expiresAt calculated using milliseconds instead of seconds.

## Evidence
src/auth/refresh.ts:42 - Math.floor(Date.now() / 1000) fixes it.

## Relevance
Any JWT/token related debugging in the future.

CLI tool

mm init              # Initialize memory directory
mm list              # List all units and records
mm read <unit>       # Read all briefs in a unit
mm search <query>    # Search briefs by keyword
mm index             # Show the index

Configuration

- id: meta-memory
  name: dsh-plugin-meta-memory
  config:
    memoryPath: '~/.dsh/meta-memory'
    enableInjection: true
    enableSkill: true
    maxBriefBytes: 4096

License

MIT -- YYTbit