Plugins

OpenViking memory and context bundle for DeepSeek Harness: pre-step auto-recall and profile injection, session capture, `viking://` URI guarding, and recall/write memory tools backed by an OpenViking server.

Memoria persistente supervisada por LLM para agentes de IA: recuperación basada en grafos, conocimiento entre sesiones, binario único. Funciona con DeepSeek Harness, Claude Code, OpenClaw y cualquier runtime de agentes.

Registers the local flowix-cli MCP server so the agent can search, read, create, and edit Flowix memos and mind-map artifacts.

PLUR memory for DeepSeek Harness — engrams injected straight into the prompt, no tool call required

Curated file-based long-term memory for DeepSeek Harness — human-readable markdown notes, one plain-file store shared across hosts (git-ignored when it lives inside a project repo), and a deterministic index cap enforced by ctx.tools.guard()

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.

Noema long-term memory plugin for DSH: durable, inspectable agent memory with recall tools and a settings page.

Integración profunda con Mnemon: memoria local de tres niveles (Runtime Memory, Documents recuperables y Memory Spaces supervisados).

Memoria entre sesiones acotada, por capas, sujeta a aprobación y auditable: una interfaz `ctx.memory` tipada con proveedor SQLite sin dependencias, una herramienta `memory` e inyección de instantáneas; cada escritura pasa por la puerta de aprobación y es reconstruible desde el registro de sesión.

Cross-session memory engine for DeepSeek Harness: SQLite store + human-editable Markdown mirror, autoDream consolidation, offline semantic search (local vector/rerank/clustering), entity-attribute-timeline, Sleep Mode, custom-model autoSummarize, and 7 memory tools.

Project-scoped cross-session memory: six-layer SQLite store (soul/user/project/fact/lesson/topic) on node:sqlite, cache-friendly first-message injection, memory_remember/search/find_similar/read/update tools, and per-window nightly consolidation ("dream").

Self-evolving team memory as plain Markdown in git: a native Cordis plugin that registers 38 bare-name memory tools plus a prompt-signals section re-evaluated at every assembly, with RPE reinforcement, decay and sleep consolidation; shares one data repo with its Claude Code (MCP) and OpenClaw hosts; verified against DSH 0.1.0-rc.6.

Memoria entre sesiones: SQLite con un espejo en Markdown editable por humanos, consolidación en segundo plano (deduplicación, fusión, resolución de conflictos) y seis herramientas de memoria.

Traslada el estado duradero de las tareas entre DeepSeek Harness, WorkBuddy, Claude Code y Codex, con puntos de control legibles por máquina y bloqueo optimista.

Semantic retrieval, resource management, auto-recall (user + agent dual spaces) and session memory for DeepSeek Harness: memsearch/memfind/memread/membrowse/memgrep/memglob over viking:// URIs, memadd/memremove resource management, memqueue observer status, memcommit session capture, and memlearn skill playbook minting.

Technical-preview local graph memory for DSH and Codex: recalls owner-global and current-project evidence before each turn, writes USER and ASSISTANT records separately, and preserves project, session, actor, and source provenance for a visual atlas and cited knowledge pages.

Long-term memory & self-evolving plugin for DSH: L0 capture → L1 memory extraction → L2 scene grouping → L3 user persona, auto recall injection, skill synthesis, fully local (SQLite FTS5 + jieba, optional vector recall).

File-based cross-session memory: plain Markdown memory files with automatic retrieval injection, format-compatible with Claude Code's CLAUDE.md and memory files, so migrating is a manual file copy.

Puente al ShiGuang Memory Engine (SGME): memoria compartida a largo plazo multiagente vía HTTP, con destilación L0/L1/L1.5/L2, inyección basada en escenarios, búsqueda unificada y señales proactivas de atención (memory_search / wiki_search / signal_pull / signal_claim / signal_ack), instalable como `dsh-sgme`.

Un vault de Obsidian compartido para todos los agentes: núcleo en Python sin dependencias (buscar/promover/adjudicar/olvidar), plantilla de vault y plugin de dsh (memory_search/show/submit/status).

Memoria local acotada con control de autoridad CBDC: afirmaciones en SQLite + FTS5, recuperación con alcance y decisiones explicables de usar/verificar/ignorar, con registro de auditoría completo, comandos /memory, inyección de ≤3 afirmaciones/1200 caracteres por llamada, sin llamadas adicionales al modelo.

Biomimetic memory system for DeepSeek Harness: plain-Markdown data layer, memory tools, frozen-snapshot injection, graded approval gating, structured audits, memory metabolism (dream), memory pins, semantic recall, /memory command, and cross-session retrieval.

Faithful port of the hermes-agent MEMORY.md / USER.md mechanism for DSH: bounded dual-bank memory (2200/1375 chars), a single `memory` tool (add/replace/remove/batch), frozen-snapshot injection per session, nudge reminders, DSH-native JSON storage — zero external dependencies, zero LLM cost.

Memoria entre sesiones con alcance de proyecto: se inyecta una instantánea de PROJECT.md en el primer mensaje del usuario, incluye una herramienta memory_remember y autorreflexión tras las tareas ReAct; cada proyecto mantiene su propio archivo de memoria.