dsh-factor-investing
A DeepSeek Harness (DSH) agent preset for institutional multi-factor stock-selection research: methodology knowledge base + zero-dependency factor statistics.
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A DeepSeek Harness (DSH) agent preset for institutional multi-factor stock-selection research: methodology knowledge base + zero-dependency factor statistics.
DeepSeek Harness plugin: a read_graph tool backed by a codebase knowledge graph (CONTAINS / EXPORTS / IMPORTS / IMPORTS_SYMBOL).
Evidence-driven learning memory and automation for Git-native AI agents
Retro macOS (System 7 / Mac OS 9) desktop UI for DSH web: chat, files, terminal, browser, docs and knowledge base inside one pixel desktop
Enterprise workbench capabilities for the DeepSeek Harness — AI employees, knowledge bases, skills, MCP servers and plugins, all managed from local state
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
Playable world-model toolkit for DeepSeek Harness: look at frames, compare pred vs GT, watch the action track, name the 3D / pixel / latent route, and RSI the research loop.
Agent negative-knowledge ledger for DeepSeek Harness: records failed paths with evidence hashes and retry conditions, auto-invalidates on evidence change.
在 DeepSeek Harness 中用自然语言搜索、保存和阅读得到大脑笔记
Learning assistant extension for DeepSeek Harness (dsh): DeepTutor tutoring for your agent — deep explanations, self-test questions, learning paths, personal knowledge-base search (RAG), and note archiving (HTTP/WS first, CLI fallback; auto-adapts local/remote deployment).
Host-only Obsidian integration for DeepSeek Harness: 25 on-demand vault, knowledge, attachment, link, editor, and command tools with an authenticated local IPC companion.
Auditable, workspace-local project wiki for DeepSeek Harness with a native Web view
DSH context-window relief: knowledge base (ctx_index/search), routing enforcement (deny flood tools), sandboxed execution (ctx_execute/batch Think-in-Code), and session continuity (post-compaction restore).
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
DSH plugin: official-model Honcho v3 memory plus a perspective-safe shared knowledge base
The claude-obsidian-derived knowledge-suite skills (wiki, wiki-ingest, wiki-query, wiki-lint, save) as a DeepSeek Harness plugin, with attribution.
DSH bundle that bridges the Codebase Memory MCP code knowledge graph into DSH and can keep indexed repositories fresh with an optional debounced filesystem watcher.
MCP server that searches the Roblox DevForum and official creator docs so AI coding agents can debug Roblox games against real community and engine knowledge.
Local knowledge bases with explicit, source-backed retrieval for DeepSeek Harness Web.
Content-addressed timeline, canon and character-knowledge evidence for DeepSeek Harness
DSH teacher plugin: Socratic tutor that leads you to answers from a markdown question set, tracks knowledge gaps in-session, and retests them on a spaced-repetition schedule.
KnowLP-RAG: dual knowledge-graph retrieval for Markdown notes — DeepSeek Harness (dsh) bundle: MCP server + native Cordis plugin
Agent-driven long-term memory for DeepSeek Harness: scoped memory (global + per-workspace), layered entries (fact/knowledge/episodic), time-bucket compaction (day→week→month→year), associative recall (related chains) + memory_relate navigation (multi-hop BFS closure), auto recall injection on user messages (CJK bigram search, tail append), agent-decided content.
Project Memory gives coding agents a single, trustworthy memory for a software repository — so they stop re-learning the same facts and stop writing conflicting "memory" files.