dsh-weneed
We Need 模式包装(DeepSeek Harness 插件):把「we need to ...」思维链引导规范(源自 scp3500/oh-we-need,MIT)做成 DSH 原生能力 —— weneed 工具(会话内一键注入)/ /weneed 命令 / WeNeed agent-preset(新会话常驻)
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We Need 模式包装(DeepSeek Harness 插件):把「we need to ...」思维链引导规范(源自 scp3500/oh-we-need,MIT)做成 DSH 原生能力 —— weneed 工具(会话内一键注入)/ /weneed 命令 / WeNeed agent-preset(新会话常驻)
Voice input for DeepSeek Harness: dictation chunked by pauses and voice messages, each with its own provider fallback chain (Deepgram, Groq, HuggingFace, local whisper.cpp, plus any OpenAI-compatible API of your own).
Real-time chain-of-thought trajectory profiling for DeepSeek Harness: live wording indicators, profile-family judgment, and per-session measurement records
Client-side writing panel for the DeepSeek Harness: project volumes, library, search, and evolution tab with inline version-chain diff and SVG thread graph.
Security review gate for DeepSeek Harness (dsh) plugins: static pre-install vetting of malicious code, vulnerabilities and supply-chain risks (with deobfuscation decoding), runtime audit, optional tool-call guard, and a one-click web review/install/uninstall panel.
Observe-only hash-chained evidence receipts for DeepSeek Harness
dsh plugin + agent preset that replicates opencode + oh-my-openagent (omo): opencode's toolchain and system prompt, omo's multi-role subagent orchestration, and browser-side omo role selection + per-role model/fallback settings.
Environment housekeeper for DeepSeek Harness: toolchain inventory, agent scratch/cache scan with safe one-click cleanup, and the machine rules file (AGENTS.md) view/edit - all in the Web GUI settings. Zero runtime dependencies.
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
Content-addressed receipts for skills actually loaded by DeepSeek Harness
Deploy the ArchGraph ARGO toolchain, skills, and rules (schema, scripts, argo-init skill, global rule) with one command.
DSH plugin: switch the language of the agent's thinking/reasoning process (简体中文, English, Русский, Français, Deutsch, Español, 日本語, 한국어 and more)
GrayPrint — live reasoning-style fingerprints for the DeepSeek Harness web chat. Compares grayscale-vs-current writing style by internal reasoning paragraphs and independently tracks Let me exploratory openers versus We need planning openers.
Audit deepseek-harness (DSH) plugins before install, guard them at runtime. Static verdict + pre-install audit protocol; supply-chain checks (typosquat, OSV); exfiltration & ransomware detection, honeypot canaries, integrity baseline. Alarm-only; blocks confirmed destructive ops.
Cross-session memory with governance, self-evolution and an approval-gated write path for DeepSeek Harness. Heat-ranked recall, environment conventions, forgetting lifecycle, supersession chains, poisoning defense, auto-distillation, and an open measurement ABI.
DeepSeek Harness plugin: hide the raw chain of thought and show a summarized chain of thought produced by a small model (any Chat Completions-compatible API).
Lint your repo for chain-of-thought leakage — the session-transcript residue AI assistants leave in docs, comments, and commit-adjacent prose. Ships the cot-trim skill as an installable DeepSeek Harness 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.
DeepSeek Harness plugin: learning agentic router — rule + UCB + LinUCB + k-NN experts under an EXP3 meta-selector, with a durable quality-reward flywheel, REAL model switching via the session request-header precedence chain, and STEP-LEVEL routing (v1.5.0)
Security for DeepSeek Harness in two layers: source-backed pre-install vetting plus fail-closed runtime guardrails and HMAC-chained audit logs. Zero runtime dependencies.
DeepSeek Harness 极简 PTC 预设:简洁提示词、run_code 工具编排、完整插件工具,以及 Windows Git Bash 和持久 PowerShell。
Two-tier model router for DeepSeek Harness — automatic execution/judgment routing with LLM Judge, multi-model fallback chains, and exponential-backoff runtime failover. A DSH adaptation of pi-shift-router.
Native memory for DeepSeek Harness — auditable facts with evidence chains, powered by StateCore
IDE engineering services for DeepSeek Harness: LSP diagnostics/navigation/rename, DAP debugging (debugpy + js-debug), and task-toolchain build/test/lint runs.