Plugins

One repository, three parts: a runtime injector for DSH plugin packages (inject, hot-reload, unload, promote a dev staging tool to the front, route self-heal, plus a settings-page plugin manager that lists, unloads and drags folders in to internalize), a task-aware reasoning-mode router agent preset (router-standard / router-spec / router-react), and a graded two-level task protocol whose six tools (commit_star, lock_stage, revise_do, edit_plan, mark_task, redteam_verdict) pin task state to disk. The injector implementation ships in-tree, so the install carries its own behaviour rather than a dependency list.

LoopX, a provider-neutral, local-first state kernel and control plane for long-horizon agents: keeps Goal, Todo, gate, evidence, quota, recovery, and handoff state above DeepSeek Harness, while the plugin bootstraps the CLI and skills, admits bounded same-session continuation, and adds a loopback GoalBar for the exact bound loop.

LoopX, a provider-neutral, local-first state kernel and control plane for long-horizon agents: keeps Goal, Todo, gate, evidence, quota, recovery, and handoff state above DeepSeek Harness, while the plugin bootstraps the CLI and skills, admits bounded same-session continuation, and adds a loopback GoalBar for the exact bound loop.

Software-engineering method pack for coding agents, with skills for baseline-first planning, systematic debugging, prompt hygiene, verification before completion, and repair/retirement tracking.

Your AI learning companion: helping you plan your studies, understand concepts, and build projects to master a subject.

Three-tier memory control plane for DeepSeek Harness: persistent runtime context, searchable project documents, pluggable long-term memory, smart routing, supervised agent workflows, WebUI, and headless tools.

DSH x Blender direct realtime plugin v1.0 — let an AI model drive Blender over a direct TCP channel: viewport frames, custom-angle renders, inner-loop search, render profiling, safe decimation, headless offload, one-call GUI launch (15 tools + blender_rt_plan: 28 families / 183 ops). 配套 skill：sixtysevenlf/dsh-skill-blender-modeling

Registers Ark Agent Plan, Coding Plan and postpaid model routes in the native DSH model picker.

Proactive associative memory for DSH: zero-prompt recall injected at a fixed boundary, three-layer auto-consolidation, skill crystallization, and Astra-style context management - handoff ledgers and a PLAN whiteboard that survive context-window switches, water-level sensing with an auto-detected model window. Local Markdown storage, model-agnostic, zero deps; lexical 0GB floor with optional semantic tiers.

Volcengine Ark provider plugin for DeepSeek Harness (DSH): registers Agent Plan, Coding Plan, and postpaid routes on the native pi-ai adapter so Ark models appear in the model picker.

Superpowers for DeepSeek Harness: TDD, debugging, planning, and collaboration skills adapted from obra/superpowers, installed as a Cordis plugin registering 14 skills with zero runtime dependencies.

Red-team engagement mode: send one target organization name and a planner session runs a five-role execution team (recon, asset triage, vulnerability discovery, exploitation, internal pivot) under a user-configurable concurrency limit (three by default, changed from the console and taking effect immediately), preflight-checking skills and resources and asking once for any missing key or VPS first, guided by a built-in first-run onboarding skill; scoring follows the merged intrusion scoring rules (8 categories / 25 points) with server-side caps, highest-privilege-wins and per-service dedup, and self-registered accounts never score — a login that fits no more specific category is scored as controlling a web application system rather than dropped; findings land in a local SQLite fact base with discovery timestamps, shown in a persistent right-side console of 9 tabs (asset mapping with a discovery timeline and the live test view, the agent roster with its concurrency setting and editable role prompts, session/tunnel state, findings — vulnerabilities, credentials and access sessions plus the attack files archived against each vulnerability — five-stage attack chain, scoring targets, an evidence-screenshot capability (register a screenshot per score point, at most three representative shots per point so a bulk result such as dozens of endpoints does not flood the console or the report, viewed inline in the console and embedded in the report, with on-site screenshots kept strictly apart from record-generated evidence cards), and a report that spells out how each score was obtained (actions, exact commands, credential provenance, tunnel build commands, a reproduction entry that is either a paste-ready HTTP request or a runnable command, plus success criteria and an evidence index), a category-organised POC/EXP knowledge base, and a skill library that reports for every unusable skill why it is unusable and the concrete steps to repair it); ships 14 reconnaissance/assessment skills (the npm package deliberately carries no tool auto-installer and no attack-chain skills — those ship as a separate toolkit Release attachment that the operator fetches and runs themselves), 56 redteam_* tools and one-command self-update.

Sidebar billing dashboard: real usage aggregated from session logs (per-model and per-day calls/tokens/cache), cost estimated in CNY from a current multi-provider pricing catalog, subscription-plan (coding/token/agent) routes exempt, and per-provider health dots.

Adds a model route where a Lead plans and reviews while a Sidekick performs code changes.

Lark/Feishu bot channel for DeepSeek Harness: each chat drives its own agent, and tool approvals, model questions, and plan reviews return as cards answered by a button or a reply. Switch workspace and model from the chat (`/cd`, `/model`, `/new`), and run several bots that keep separate sessions and can hand turns to each other in one group.

Personal assistant for DeepSeek Harness that turns conversational commitments into cross-session plans, reminders, and an auditable dashboard.

DSH notification & remote-control plane: one `notify()` API across 28 outbound channels, six inbound control channels, phone approvals/questions/task control, a Native DSH Notify & Control UI, live outbound hot-apply, multi-agent routing, and zero runtime dependencies.

Remote control for dsh web from a phone browser, from anywhere (no public IP needed): hosted cloud relay works over 4G, or self-host the router; one command installs the desktop bridge and this in-harness Settings panel (cloud/self-hosted tabs, account login, bridge start/stop, feedback); the tunnel data plane is end-to-end encrypted (E2EE phone↔desktop, with a QR / one-time-link desktop grant so you never re-type the password), with HTTP/WebSocket pass-through, access-key auth, a live device list and optional traffic quotas.

Installs four multi-agent math-research presets for DSH: v2 (probability-driven pipeline with multi-verifier debate), v3 (paper-style Markdown knowledge base with a planner agent and a reusable method library), v4 (persistent self-organizing residents that message and meet), and v5 (a research institute with an academician who decomposes and assigns work, voting researchers, temp workers, group chat and a compare-and-set task board); all four support checkpoint resume, human intervention, and an optional Lean formal-verification switch (off/encourage/require) whose passing proof turns the vote into a fidelity check of the Lean statements.

Notification reminders, message alerts and desktop notification for DSH — a desktop notifier that raises a system toast, a sound and a tab-title marker when the agent needs your input (approval, plan review, question) or a reply is finished in the background (task complete / completion alerts, notify when done); the Settings page holds the master switch, sound and volume, the per-case toggles and the zh/en notification language.

Complete port of obra/superpowers for DeepSeek Harness: 14 methodology skills via a native SkillProvider (rank 550), covering brainstorming, planning, TDD, debugging, parallel agents and more, with Chinese-localized docs and zero-build install.

Engineering workflow system for AI coding agents — mandatory planning, TDD, verification, review, and intelligent codebase graph analysis.

Paper reading workbench: library + PDF reader + tutor-style companion. Answers cite clickable page numbers that jump back to the PDF and flash the exact passage; select-to-ask without leaving the paper; bundled strict-tutor preset (reading plan, section coaching, graded quizzes tracked across sessions); in-place original ↔ Chinese toggle (babeldoc, zero preinstall). Local transcription and search — documents never leave your machine.

Local-first code knowledge graph for coding agents: 10 MCP tools for layered context compression, DAG planning, incremental AST indexing, a cross-session skill flywheel, diagnostics, and graph artifact import/export.