dsh-oomol
OOMOL Connector integration for DeepSeek Harness: connect apps and call Actions through progressive MCP discovery.
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OOMOL Connector integration for DeepSeek Harness: connect apps and call Actions through progressive MCP discovery.
Structural code intelligence for DeepSeek Harness (dsh) — gives the agent codegraph and codegraph_index tools to find where a symbol is declared, what calls it, and what a change reaches, from a tree-sitter index it builds itself. Compatible with the codegraph CLI's on-disk format.
Bring any file into the conversation — stashed to the workspace and referenced by path; zero type rejection
DSH agent preset: chief coordinator + 17 domain-expert subagents with taskboard scheduling, quality gates, and real inter-expert communication bus (专家模式)
从规划到发布的 DeepSeek Harness 插件全流程指南,覆盖需求与形态决策、脚手架生成、业务实现、本地验证、发布准备和最终发布。Use when the user wants to plan, create, bootstrap, develop, verify, or publish a DSH plugin/extension, or asks how to build a DeepSeek Harness plugin end-to-end.
Expose DeepSeek Harness agent capabilities as an MCP server, so an external MCP client (e.g. Hermes) can drive Harness to execute coding tasks. Hermes = brain, Harness = arms.
TaskPack: an open, offline task-handoff container. Task Passport is the durable state; TaskPack is the box it travels in.
DSH Studio: a local Desktop and Web workbench over DeepSeek Harness
Reduce large agent tool output by what it means, not by where it was cut.
OpenViking retrieval, resource management, auto-recall and session memory for DeepSeek Harness.
DeepSeek Harness 长期记忆与自进化插件:L0 对话捕获 → L1 记忆提取 → L2 场景归纳 → L3 用户画像,自动召回注入 + 技能合成,纯本地。
Unified DeepSeek Harness plugin: role-based subagent routing + per-agent evolution — prefercmd/memory as knowledge allow/deny lists, so repeated tasks start from proven commands and save tokens
MiniMax multimodal bridge for DeepSeek Harness (DSH). One mmx_bridge tool covers describe/image/video/speech/music/cover/search/quota; optional web_search/read_image takeover; built-in client enhancement renders inline players/previews plus a settings-page management card in the Web GUI.
DeepSeek Harness bundle for the aiworkskills WeChat article workflow
Standalone DeepSeek Harness plugin: continual harness self-evolution. The agent persists and refines reusable prompt notes, memories, skill contracts, and subagent specs through small evidence-backed edits, with automatic refinement gates, rollback, and prompt injection.
Codex conversation backend for DeepSeek Harness, powered by the Codex App Server with approvals and DSH tool support.
DSH Mini TUI: a minimalist terminal interface plugin for DeepSeek Harness
Runtime requirement drift guard for DeepSeek Harness — keeps long-running agents aligned with user intent while they work.
Local-first persistent memory infrastructure for DeepSeek Harness: bounded hot-memory bootstrap, explainable cold recall (exact + Chinese BM25), lease-lock transactional writes, read-only governance, and trajectory review. DSH plugin host; Python stdlib + Markdown core. Zero database / vector service / external service dependencies.
Local PDF, Office, image, and OCR document intelligence for DeepSeek Harness.
Self-evolving memory + skill lifecycle for DeepSeek Harness. Cross-session memory with zero-token deterministic recall (bigram-Jaccard fused with FTS5 BM25 via RRF), a tiered approval gate, and reinforcement that strengthens what you repeat. Procedural knowledge crystallizes into SKILL.md files that refine in place and are curated through an active-stale-archived lifecycle (reversible archive, pre-op backups, rollback, never deletes). Includes background per-turn review, anti-bloat convergence for both skills and memory, an auto-grown user profile, and a web settings page.
DSH US stock market data plugin, powered by yahoo-finance2
AI-for-Science research workflow skill bundle for DeepSeek Harness: multi-angle literature review with per-angle files, anchored experiment design with a caveat list, figures, paper reading; cross-verification briefs.
创建、运行和续玩仅限虚构成年人的沉浸式互动叙事,支持完整随机开局、张力引擎、身份与处境生成、NPC独立决策、时间推进、事件队列、世界追算和可恢复存档。仅当用户明确要求创建或续玩此类叙事,以及其存档、开局或世界推演时使用;不用于无关的总结、存档、角色扮演或世界推演。