Awesome DeepSeek Harness Plugin

Native conversational image generation for DeepSeek Harness: ask the agent to create an image, and it handles generation and keeps the result directly in the conversation.

AgentTeams multi-agent teams.

Runs scheduled coding tasks in isolated DeepSeek Harness sessions, managed from Settings or the agent.

Task ledger: a dsh plugin that has the agent create, claim, advance and close tasks, writing each step straight into a plain-text ledger in the workspace so the owner, the current state and the next step stay on record; no cloud service is involved, single-user and multi-user both work with Git synchronisation, and a control panel summarises in-flight, overdue and stalled work with weekly trends.

Lets the agent start a conversation on its own, using a local dice roll on a set interval to decide whether to speak into a chosen session, with quiet hours and a dry-run mode.

Schedules a daily, weekly or monthly GitHub Trending digest, has a local trendradar core write Chinese summaries and period recaps, commits them to your own repo and opens the pull request, and shows an overview, digest, run history, subscription and settings workbench.

Scheduled cron tasks, background automation and agent execution for DeepSeek Harness.

Novel-writing guardrails: 20 novel_* tools enforce fact-ledger consistency, phase and chapter gates, machine audit with deterministic metrics, and proposal-only revisions; a right-panel workbench covers reading, TTS playback, polish, proofread, continuity checks and batch drafting, and a bypass engine runs internal steps off the main conversation.

Novel-writing workbench for DSH with an authoring preset, outline and character management, manuscript annotations, review workflows, and a managed local Python backend.

AgentCompare provides A/B workflows for one Vite task in DSH: run two implementations, compare live previews with shared checks, choose blind, and review adoption against current project edits. Requires a root-level Vite project in a Git repository with at least one commit.

Defines multi-agent team rosters as YAML or JSON files, validates them, bridges each member into dsh-agent-teams member arguments, and verifies the result against the running team.

Task board for DSH: create tasks with project and model assignment, run them manually or on cron schedules; new sessions in a project automatically pick up its todo tasks and move them to in-review when done.

All-in-one combo patch for STARDUSTLC's 18 DSH plugins: one command injects shared default configs across office, media, DevOps and notification presets; each component installs directly via a one-line add command (flat design, no git subdependencies).

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

Deep reading & summarization for DSH: books/papers/videos/web into structured Obsidian notes via plugin parsers, MapReduce parallel deep-read subagents, JSON Schema outputs and an idempotent cache.

Let Claude Code or Codex do the thinking: understand the request, write a clear prompt for DeepSeek Harness to do the work, and review the result. dsh-baton runs your tests itself, lists what changed, and has a sub-agent check every requirement, so your main model only reads the result and decides. Codex waits in one call of up to 59 minutes, with no hook to trust and nothing to poll; you can change the request while it runs, and name the Harness model for a task. On big jobs it saves most of your plan's quota.

Durable task-decomposition plans for DeepSeek Harness with a self-learning loop: every department subtask runs in three ordered phases (plan, execute, verify), the verify phase must submit a retrospective of problems, detours and resolutions, and that retrospective is written to a permanent lessons file, ranked against the new subtask and injected into later dispatches so the same mistake is not repeated. Adds a read-only dsh_workplan_lessons tool (11 model tools in total), a progress panel drawn as a ring, a stacked bar and per-stage steps, and a public ISO/IEC 15408:2026 security self-assessment with zero runtime dependencies.

Declarative DAG runtime for DSH tool plans with bounded parallel execution, read-only retries, per-step checkpoints, cancellation, and conservative crash recovery.

Verifiable research-report engine for DeepSeek Harness with a content-addressed evidence ledger, versioned sealed reports where every claim carries a verification verdict and the manifest hash seals the directory, and retrieval orchestration that reuses the ctx.web and ctx.jobs seams.

Multi-agent orchestration agent preset for DeepSeek Harness: one chief orchestrator that never implements itself — it triages every request, has a PM expert plan the work, and delegates implementation to domain experts via a merged expert roster (list and summon tools), scheduling parallel work through a dependency-DAG taskboard and a file-based message bus, with delivery gated by an independent review. Ships 11 core experts; more expert teams (Agency agents EN/ZH, classic collections) are one-click downloads from the settings page over dual GitHub/CDN channels with sha256 verification. Published on npm as dsh-expert-orchestrator (requires DSH >= 0.1.7-alpha.2).

Recursive delegation for dsh agent trees: a preset plus Host limits bound what each subagent may do, subagents work in separate _agents/ workspaces, and the parent decides which results to integrate.

Skill-driven harness/loop engineering workflow agent plugin.

Pair a second model that passively reviews each turn and injects notes.

Cuigengji, your fiction-writing assistant and editor: organize settings, develop plots, draft chapters, and revise prose with AI. Share plot canvases, character cards, and worldbooks while you choose the direction, style, and what stays in the story.