deepseekplugins

DeepSeek Harness plugin

dsh-skill-lord-serf

DeepSeek Harness plugin: Lord/Serf agent protocol 0.5 skills (file-based multi-agent orchestration with bounded execution and schema-validated submissions)

Workflow & Automation
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Source facts

Repository
ttxl314/dsh-skill-lord-serf
Latest update
Aug 14, 2026
Category
Workflow & Automation
GitHub stars
1
Format
plugin
Catalog evidence
Upstream dsh.bundle evidence
Evidence path
package.json#dsh.bundle
Checked against
0.1.0-rc.8
Upstream check date
2026-08-20

This evidence comes from the upstream catalog. This site has not installed, run, or security-reviewed the plugin.

Install

Start with a prompt that asks an agent to review the GitHub repository and source. Switch to the command if you want to install it yourself.

Copy this prompt into DSH, Codex, or another agent and ask it to review the GitHub repository and source first.

Do not install or run any commands yet. Read this plugin's GitHub repository, README, and relevant source code. Then answer the questions below clearly and directly so I can decide whether it fits my needs:

1. What is this plugin, and what problem does it solve?
2. Who is it for, and what are its typical use cases?
3. How is it used after installation? Include one minimal example.
4. What known limitations or privacy, security, compatibility, or maintenance risks does it have?
5. Give a clear recommendation: recommend, conditionally recommend, or do not recommend, with reasons.

Distinguish statements documented by the repository, inferences from source code, and unknowns. If evidence is insufficient, say so explicitly. Do not guess or simply repeat the README.

GitHub: https://github.com/ttxl314/dsh-skill-lord-serf
Plugin: dsh-skill-lord-serf
Author: ttxl314

Check the source files

Read the README and other files from this plugin directory before installing.

File explorer4 files
README.mdSource · read only
README language

@ttxl314/dsh-skill-lord-serf

English | 中文

A DeepSeek Harness (DSH) plugin port of ttxl314/lord-serf-agent-protocol-SKILL (protocol 0.5): it ships the lord and serf skills so DSH can act as the Lord (orchestrator) and as the Serf (executor).

The protocol

A file-based multi-agent orchestration protocol with the lifecycle:

plan → package → dispatch → execute → submit → review → decide
  • Lord owns planning, task packages, Serf dispatch, the authoritative task state source, review decisions, and final acceptance.
  • Serf owns bounded execution of one Lord-issued task package, self-validation of actual outputs, and one submission report (REVIEW / BLOCKED / CHANGE_REQUEST).
  • Chat is notification only; project state, requirements, evidence, and decisions live in files (TASKS.md, TASKS/, REVIEWS/, BLOCKERS/, CHANGE_REQUESTS/).

Repository structure

dsh-skill-lord-serf/
├── package.json          # dsh.bundle manifest; no runtime deps, peers only
├── cordis.patch.yml      # bundle patch layer: registers the plugin row
├── lib/index.js          # cordis plugin: file-backed provider on ctx.skills
├── test/self-test.mjs    # self-test suite
└── skills/
    ├── lord/
    │   ├── SKILL.md          # DSH-adapted (DSH Bindings mapping table)
    │   ├── assets/schemas/   # task-package / micro-task / dispatch-instruction schemas
    │   ├── assets/templates/ # task-package / dispatch-instruction / project templates
    │   └── references/       # scaling, review, change control, recovery, adapters, ...
    └── serf/
        ├── SKILL.md
        ├── assets/schemas/   # submission-envelope / review-report schemas
        ├── assets/templates/ # REVIEW / BLOCKED / CHANGE_REQUEST templates
        └── references/       # intake, subagent fan-out, self-validation, reporting, ...

Each skills/<name>/SKILL.md carries DSH skill frontmatter (name + description), so one file serves two installation paths:

1. Plugin: at startup lib/index.js registers a file-backed provider on ctx.skills (rank 250) exposing both skills with resourceBase: { kind: 'directory', path: <skill dir> } in the global layer, available to every session. get() re-reads the body on every load, so content edits take effect immediately. 2. Filesystem: copy (or link) skills/lord and skills/serf into <project>/.dsh/skills/ or ~/.dsh/skills/; dsh-skill-filesystem discovers them without a restart.

DSH bindings

Protocol conceptDSH mechanism
Serf executorsubagent tool (one subagent per task package) or a separate DSH session
Serf sub-work fan-outsubagent tool for bounded, disjoint sub-steps inside the task boundary; see skills/serf/references/dsh-subagents.md
$serf invocation/serf user gesture, or a skill(name='serf') call inside the dispatched subagent
$lord review <path> / $lord resolve <path>/lord gesture plus the report path; a subagent Serf's final message already reaches Lord
State source / packages / reportsPlain workspace files read and written with the filesystem tools
Long-running orchestrationDSH goal tools

Install

A. As a bundle (global)

Install from GitHub — this package ships prebuilt ESM, so there is no build step and no prepare-script permission to grant; pinning a commit is recommended:

dsh plugin --profile <name> add github:ttxl314/dsh-skill-lord-serf#<commit-sha>

Or link a local checkout:

dsh plugin --profile <name> add ./dsh-skill-lord-serf

dsh plugin adds the package to the profile's dependencies and dsh.profile.bundles; the bundle's own cordis.patch.yml registers the plugin row. Restart the web service afterwards; the entry then appears in the GUI's Settings → Plugins inventory.

B. As filesystem skills (no restart, project-scoped)

New-Item -ItemType Junction -Path .dsh\skills\lord -Target <checkout>\skills\lord
New-Item -ItemType Junction -Path .dsh\skills\serf -Target <checkout>\skills\serf

The skill watcher picks the catalog up immediately.

Usage

  • Lord session: say "orchestrate this project with the Lord protocol" or type /lord; follow the workflow to produce task packages and dispatch instructions and maintain TASKS.md.
  • Dispatch a Serf: Lord dispatches through the subagent tool; the subagent prompt is the generated assets/templates/dispatch-instruction.md, and it must load the serf skill before executing the task package.
  • Serf session: type /serf or hand it a task-package path; it may fan out sub-work through subagent inside the boundary (references/dsh-subagents.md), then writes the report from a template and ends with the report path.

Self-test

node test\self-test.mjs

The suite runs 26 checks: provider contract (apply/list/get/invalidate), SKILL.md frontmatter parsing, residual Codex-marker scan, existence of every referenced resource path, compilation of all 6 JSON Schemas (draft 2020-12), positive and negative representative payload validation (including v0.3 field rejection), and template/schema const agreement. It resolves ajv, ajv-formats, and yaml from the local DSH profile ($DSH_HOME).

An end-to-end drill is also supported: Lord creates a schema-validated task package → a subagent loads the serf skill and executes → the report passes the micro-review-report/submission-envelope schemas → Lord verifies actual outputs and updates the authoritative state.

Dependencies

  • @deepseek-ai/cordis ^4.0.1 (peer)
  • @deepseek-ai/dsh-skill ^0.1.0-rc.6 (peer, provided by the @deepseek-ai/dsh-base bundle)

Differences from upstream

  • All $lord/$serf (Codex commands) → /lord//serf (DSH skill gestures).
  • dispatch-instruction's worker_invocation const is /serf; the Invocation section describes DSH subagent dispatch; Execution Requirements gained a subagent fan-out clause.
  • Added serf/references/dsh-subagents.md (DSH-specific Serf fan-out rules) and an "Execution Capabilities (DSH)" section in the coding adapter.
  • Removed the Codex-only agents/openai.yaml.
  • The protocol itself (field names, micro/standard/full task profiles, status vocabulary, report paths, non-negotiables) matches upstream 0.5 exactly, so task packages and reports remain interoperable across platforms.

License

Derived from ttxl314/lord-serf-agent-protocol-SKILL (MIT); this port is released under the same [MIT](LICENSE) license.

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