34 results
Reflect2Evolve memory plugin: layered L1/L2/L3 memory, reflection-weighted value backprop, cross-task policy induction, skill crystallization, and three-tier retrieval for OpenClaw, Hermes Agent, and DeepSeek Harness.
Multi-provider Web Search & Fetch for DeepSeek Harness — 8 deeply adapted providers, SearchHints, resilient fallback, and native X / Xiaohongshu retrieval
OpenViking retrieval, resource management, auto-recall and session memory for DeepSeek Harness.
Headroom-inspired automatic context compression plugin for DeepSeek Harness (dsh): compresses tool outputs before they reach the model and keeps every lossy compression reversible via CCR retrieval tools.
A general-purpose knowledge base plugin for DeepSeek Harness (DSH): import documents (md/txt/json/yml/docx/pdf), organize them in folders, and search with FTS5. 通用知识库插件：文件导入、目录化管理、全文检索、知识库管理 UI。
Obsidian side-panel math memory agent for DeepSeek Harness: layered long-term memory, idea memo with proactive review reminders, unified note_recall retrieval plus dedicated note search/create/backlink tools. Ships as both a dsh plugin and an Obsidian community plugin.
DeepSeek Harness plugin — manage an LLM-Wiki knowledge base from the agent: wiki_search / wiki_read / wiki_stats / wiki_validate / wiki_fix / wiki_errorbook / wiki_ingest
Conversation history recall for DeepSeek Harness: search the original text of every session (like searching chat records) — literal/fuzzy/semantic retrieval, fully local & offline. AI never forgets what you told it.
AiFP Cognitive Memory — persistent memory MCP server for AI assistants. Chinese-first retrieval with causal chains, Hebbian associations and graph diffusion. 记忆感知系统
RAGFlow knowledge-base retrieval capability for the DeepSeek Harness — the ctx.ragflow Service Definition, an HTTP Service Provider, and the model-facing ragflow_retrieve tool
Persistent 5-layer memory system for DeepSeek Harness (entry injection, relevance retrieval, agent tools, and LLM-backed auto-extraction).
Local knowledge bases with explicit, source-backed retrieval for DeepSeek Harness Web.
KnowLP-RAG: dual knowledge-graph retrieval for Markdown notes — DeepSeek Harness (dsh) bundle: MCP server + native Cordis plugin
Long-term memory for DeepSeek Harness: multi-channel retrieval and an evolving memory store.
Thin on-demand context-retrieval layer for DeepSeek Harness: context_query / context_slice / context_grep tools over the sessionQuery and subprocess seams.
dsh bundle: local semantic index over workspace documents (MD/PDF/DOCX/TXT) with FTS5 BM25 + local embedding hybrid retrieval, hit citations with line numbers, and incremental updates.
dsh 插件开发知识库：DeepSeek Harness 官方文档站完整 Markdown 镜像（中英双语 184 页）+ 58 篇仓库补充开发参考 + 主题导航与 245 文件全量搜索索引；以 dsh-plugin-dev-kb 技能让 agent 在插件开发任务中自动加载定位文档。纯数据插件，零运行时依赖。
Persistent memory for DeepSeek Harness: per-conversation notes, selective injection, project memory, semantic Vault search (bge-m3, free optional key) and automatic retrieval — agents stop forgetting.
Notebook Knowledge Studio — NotebookLM-like local knowledge workspace for DeepSeek Harness: Notebooks, Sources, source-grounded Chat with citations, and Studio artifacts (Mind Map / Reports / Flashcards / Quiz / Infographic / Slide Deck / Data Table), stored as OKF v0.2 markdown under the workspace.
Cross-session long-term memory for DeepSeek Harness: dual-scope SQLite memory graph, hybrid retrieval, provenance audit, and a knowledge flywheel.
DeepSeek Harness (DSH) plugin: a self-contained semantic memory (RAG) over all your chat sessions. Indexes messages live via session/event, stores embeddings in one local JSON file, and exposes a rag_search tool.
Local-first, source-linked Markdown wiki storage and retrieval plugin for DeepSeek Harness
Pre-write reuse firewall for DeepSeek Harness: before the agent writes a new helper/service, surface the existing implementations that already cover that intent. Deterministic retrieval (no LLM) backed by the Auto_code_audit capability channel.
Cloud-backed cross-session memory for DeepSeek Harness: structured entries + vector retrieval persisted to S3-compatible object storage (AWS S3 / MinIO / R2 / OSS), with local cache projection, approval-gated writes and auditable trails