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Expert Orchestrator — DeepSeek Harness 插件(DSH Plugin)
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dsh-expert-orchestrator

Expert Orchestrator

专家编排模式 agent preset — 首席编排者:每条消息先归类分诊、PM 先行规划、合并花名册优先委派、任务板依赖调度、消息总线并行落盘、分级交付门禁、经验池按需沉淀。

插件会安装到这里;不确定时保持 web。

npx -y @deepseek-ai/dsh plugin --profile web add github:mario841859784/dsh-expert-orchestrator#457fc99547a0e23effc17bfd250b5deff87f9ba9
README兼容性版本

兼容性与来源证明

Expert Orchestrator 以 dsh-expert-orchestrator 发布,当前版本为 2.3.0。Plugin Hub 会校验它的 manifest,并保存精确安装来源,便于复现安装结果。

DSH 兼容范围
*
运行环境
web
发布来源
github
Registry 更新时间
2026/9/19

版本

2.3.0stable
2026/9/19
2.2.0stable
2026/9/18
2.1.2
stable
2026/9/18
查看其余 2 个版本收起版本
2.0.0stable
2026/9/18
1.5.0stable
2026/9/18

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最新版
2.3.0
DSH
*
HMR
重启进程
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未声明可安全裁剪
解包体积
未提供
文件数
未提供
Surface
web
许可证
MIT
发布源
github
GitHub
★ 1
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0
最近提交
2026/9/18
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Agency Agents@michengai/dsh-agency-agentsAgency Experts — 可召唤的领域专家名册,适用于 DSH(专家模式)Headless@deepseek-ai/dsh-headlessdsh one-shot bundle:基于 dsh-base 的直接核心 Agent/Session 运行器,不包含 Host、HTTP 或浏览器层Automation@michengai/dsh-automation在独立 DSH Session 中按计划执行编码任务,支持 Web 设置页与 Agent 双入口管理。Auto Reviewdsh-auto-review针对 DeepSeek Harness 审批请求的第二模型 AI 自动审查:只读审查子代理在审批应答链上决定允许或拒绝,并采用故障关闭回退机制和完整的会话日志审计。

README

DSH Expert Orchestrator

PM-first planning · merged-roster delegation · gated delivery · experience pooling

A DeepSeek Harness (DSH) agent preset plugin: once installed, DSH gets an "Expert Orchestrator" session mode that never implements changes itself — it triages every request, has a project-management expert plan the work, delegates implementation to the best-fit domain experts, and gates delivery with independent review.

中文文档


How it works

  • Per-turn triage + five anchors — every user message re-enters the loop (large task / small implementation / read-only); the five-anchor self-check runs before every action (review | converge | anti-drift | collaborate | resources) to prevent cross-turn drift.
  • PM first — complex tasks go to a project-management expert (decomposition, dependencies, acceptance criteria) before any delegation.
  • Delegation only — implementation is always delegated (merged expert roster first — bundled core + enabled sources — with the bundled expert-prompt library as fallback); the orchestrator only verifies read-only.
  • Taskboard + message bus — two zero-dependency Python tools: a dependency-DAG task scheduler and a mailbox bus so parallel experts hand off full output on disk while replying with short summaries.
  • Delivery gate — independent reviewer (≠ implementer, ≤2 rework rounds) then a PM checkpoint before any commit/delivery.
  • Experience pool — ≤3 reusable lessons captured per task and injected into future task briefs.
  • Native expert tools — list_experts (browse the merged roster, compact/expanded modes), summon_expert (single white-paper summon: persona injected via sanitizePersona, resolution exact → aliases → unambiguous title, shadowed/disabled rejected, 8K-char task cap), and summon_experts (batch ≤8, concurrency 4, partial-success semantics). Recursion protection: spawned sub-agents get a six-entry toolFilter deny list (no expert-tool re-summoning, no subagent/subagent_fork nesting, no workflow) with the tool schema default depth 3 as a backstop — one level of delegation, no runaway expert trees.

Install

dsh plugin --profile web add github:mario841859784/dsh-expert-orchestrator

or manually copy agent.cordis.yml, preset.yml and skills/ into ~/.dsh/.agent-presets/expert-orchestrator/, then restart DSH and pick the preset. Requires python3; the dsh-agency-agents roster plugin is optional coexistence, not a dependency — this plugin no longer depends on it: the merged-roster protocol works fully without it, and when it is installed its roster is treated as just an additional source. The bundled trim-cli skill's scripts wrapper and bin binary are not part of this package (excluded from the files whitelist); fetch them separately per the trim-cli skill docs.

After install, only the 11 bundled core experts ship in skills/expert-orchestration/experts/. The four upstream expert source packs are not bundled — download and enable them from the plugin's settings page (Expert sources): the host runtime fetches via the GitHub direct or CDN mirror channels and verifies sha256 (pinned archive hashes) before unpacking anything. Install-time security scans (credential-leak + prompt-injection patterns) are tiered by origin: for registry sources (sha256-pinned), a scan hit raises a warning and proceeds only after explicit user confirmation — never auto-rejection; custom/local-path sources outside the registry are hard-rejected on a hit; symlinks are always skipped and logged, never a rejection on their own.

Expert management is per-expert: any single expert inside an installed source can be disabled individually (files stay, re-enable anytime), and the settings page lets you create/edit/soft-delete up to 200 custom experts — custom experts rank just below bundled-core and take precedence over source-pack duplicates when chosen as the dedup representative; built-in and source-pack experts are read-only references (copy to a custom expert to modify); custom prompts are user-written, skip third-party source scanning, and are subject to length limits.

The deployer never deletes anything in the target directory, refreshes protocol files only on version bumps, and treats lessons.md and expert-sources/ (downloaded source packs + merged roster view) as user data (add-only).

Local source self-deploy (optional)

A market/plugin-manager install (dsh plugin --profile web add github:mario841859784/dsh-expert-orchestrator) mounts the deployer automatically via bundle patch — no manual composition entry is needed.

Only if you want to load the plugin from a local source checkout, patch the host layer instead (same mechanism as dsh-onebot): insert the following into ~/.dsh/profiles/<profile>/cordis.patch.yml:

- insert:
    - id: expert-orchestrator-deploy
      name: '/absolute/path/to/dsh-expert-orchestrator/lib/index.js'

Upgrade semantics: when the plugin VERSION changes, the installed package content overwrites the PROTOCOL files (agent.cordis.yml, preset.yml, skills/expert-orchestration/SKILL.md, skills/expert-orchestration/routing.md, skills/expert-orchestration/tools/taskboard.py, skills/expert-orchestration/tools/bus.py, skills/trim-cli/SKILL.md, skills/trim-cli/manifest.json, skills/trim-cli/entries, skills/trim-cli/reference — 10 items in total), plus skills/expert-orchestration/experts/ which now ships only the 11 bundled core experts (PROTOCOL refresh). USER_DATA (lessons.md, expert-sources/ — downloaded source packs and the merged roster) is only created when missing and never overwritten; on first run after this version, previously adapted expert copies are migrated once into expert-sources/legacy-adapted/ (frozen local source, enabled by default) instead of being deleted. A host-layer local mount is not affected by that overwrite.

Migration note for existing installs: if you previously added an expert-orchestrator-deploy entry manually in agent.cordis.yml, migrate it to the host-layer cordis.patch.yml before upgrading — otherwise a VERSION-change refresh will overwrite that entry with the factory copy, silently breaking the local mount.

Expert source projects

Expert content beyond the 11 bundled core experts comes from four MIT-licensed upstream projects. All four are registered in skills/expert-orchestration/source-registry.json and referenced verbatim — file names and contents unchanged (files are unpacked as-is; attribution lives in NOTICE):

ProjectLicenseAdoption in this pluginPinned files
VoltAgent/awesome-claude-code-subagentsMITClassic pack content source — anchors the previously adapted expert copies in the offline classic pack (62 files)171 (categories/**/*.md)
wshobson/agentsMITClassic pack content source — anchors the previously adapted expert copies in the offline classic pack (4 files)202 (plugins/*/agents/*.md)
msitarzewski/agency-agentsMITStandalone source pack — installed whole as an independent source274 (*/*.md)
jnMetaCode/agency-agents-zhMITStandalone source pack — installed whole as an independent source273 (*/*.md)

Counts are the unpacked file numbers actually selected at each pinned ref after applying the registry include/exclude patterns (verified against the pinned archives' sha256).

The first two are the content sources of the classic pack (the offline fallback release anchoring the 67 previously adapted expert copies); the latter two ship as independent source packs. Downloads go through the GitHub direct or CDN mirror channels with sha256 verification and tiered install-time security scanning (tiering rules see the deployment section above); installed sources appear in the merged expert roster as source-name / original-name, and cross-source duplicate names coexist with explicit source labels. All upstream projects are MIT-licensed; expert texts remain copyrighted by their authors, redistribution here follows MIT with attribution.

Recommended configuration (Chinese-language users): enable awesome-claude-code-subagents + agency-agents-zh as the source set — together with the 11 bundled core experts they cover the common routing table entries with Chinese-native expert texts; add the other sources only when you need them. Decoupling statement: this plugin no longer depends on dsh-agency-agents — the merged expert roster (bundled core + enabled sources) is the primary supply for expert selection; the protocol is fully usable with dsh-agency-agents uninstalled, and when it is installed its roster counts as an additional source the protocol does not require.

Credits

  • DeepSeek Harness
  • MichengAI/dsh-agency-agents — optional Agency expert roster (coexistence supported, not a dependency)
  • Asher-2000/dsh-expert-mode — inspiration for the five-anchor check, experience pool, independent review, taskboard and message bus
  • VoltAgent/awesome-claude-code-subagents · wshobson/agents · msitarzewski/agency-agents · jnMetaCode/agency-agents-zh — imported expert library sources (MIT)

MIT © mario841859784