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mstar-harness

btspoony/mstar-harness

Skill-driven harness/loop engineering workflow agent plugin.

493TypeScriptMITSource

Install

Add mstar-harness to DeepSeek Harness

via GitHub · GitHub source

Installing from GitHub runs the project's build script, which pnpm blocks until you allowlist it — run the command once and pnpm prints the exact key to add under `allowBuilds` in ~/.dsh/profiles/web/pnpm-workspace.yaml.

What happened when we ran it

Installed cleanly when we ran it

Every command here is run in a throwaway container against a clean profile, and the result is whatever the harness recorded — not a guess from the source. Last run 2d ago.

Due diligence

Before you install mstar-harness

  • Source of record: btspoony/mstar-harness — present in the community registry that DSH's own plugin market installs from.
  • Licensed under MIT.
  • Detected: install script, terminal surface. Read the source before granting these.
  • A listing here is not a security review. Plugins run with your agent's permissions.

The AI take

What it is — Morning Star Harness is a TypeScript Harness Workflow Engine Agent Plugin that enforces deterministic workflow gates and provides mstar-* judgment skills.

Who it is for — When performing iteration or codebase audit in DeepSeek Harness for multi-agent code delivery, it fits. If your tasks do not involve judgment skills for engineering loops, you don't need to install it.

Watch out — From source install you need to manually whitelist the build script. It automatically executes scripts and runs shell commands. Sandbox test passed: installed in new profile and registered by harness, no obvious issues found.

The verdict — I would install it because it provides a portable engine across multiple hosts.

Generated by grok-4.6, and a starting point rather than a verdict. Where it says a plugin installs or does not, that is from a real run in a clean profile — everything else is read off the repository. Trust the source over this.

What mstar-harness does

Abstract diagram of plans passing through deterministic gates into a checked workflow.

mstar-harness is a DeepSeek Harness plugin that provides a skill-driven workflow engine for planning, implementing and checking code changes. DeepSeek Harness uses the plugin’s Agent Plugins v1 package, including plugin.json and skills/, while the TypeScript @mstar-harness/engine applies workflow gates for paths, status, leases, dispatch, SDD, iteration and linting. The mstar-* skills supply role-specific judgement and workflow decisions rather than leaving those rules solely in prompts.

The package also includes @mstar-harness/cli, which provides the mstar-harness and mstar commands for engine checks and host setup. Typical flows are a per-plan Prepare → Execute → QC → QA gate → Done cycle, an iteration running through Phases 1–5, or the read-only /codebase-audit flow, which writes plans under {PLAN_DIR}/audit-<date>/. Setting enforcement: hard in an iteration compass makes dispatch preflights fail fast; otherwise, checks remain advisory.

mstar-harness is intended for teams that want a prescribed, multi-agent delivery workflow across DeepSeek Harness and other supported hosts. It is a poor fit for lightweight sessions that do not need planning or gate enforcement, or for environments that cannot use the package’s terminal-facing CLI. Installation and bootstrap can run scripts and independent plugin installs, and the workflow can invoke terminal commands in the agent’s available permissions. The short mstar executable also conflicts with an unrelated npm package of the same name.

mstar-harness documentation

Configuring mstar-harness

DeepSeek Harness loads the portable Agent Plugins v1.0.0 package from the repository root through plugin.json and skills/. The dsh setup described by the README uses the @mstar-harness/dsh adapter and can also install dsh-llm-fallbacks independently. The optional engine CLI is installed globally as @mstar-harness/cli; its canonical executable is mstar-harness, with mstar as a short alias.

The documented workflow setting is:

Key Effect
enforcement: hard Makes dispatch preflights fail fast instead of leaving engine checks advisory

This setting belongs in an iteration compass. The README does not specify a default value for enforcement.

mstar-harness Commands

The CLI exposes workflow validation commands cited by the skills, including mstar status validate, mstar dispatch validate and mstar iteration gate. Use mstar-harness instead of mstar when the shared executable name is ambiguous. npx @mstar-harness/cli doctor --target <opencode|cursor|codex|zcode|omp|dsh> checks a host setup, while npx @mstar-harness/cli plugin validate validates the portable package.

Workflow entry points include /iteration-start [direction] [pause], /iteration-drive, /iteration-loop [direction] [scale], and /codebase-audit [keywords]. scale accepts S, M, L or XL, defaulting to M; audit effort accepts quick or deep, with standard as the default. Audit output is read-only and goes to {PLAN_DIR}/audit-<date>/.

How mstar-harness behaves

DeepSeek Harness can enter the project-manager workflow through the pm skill, which is not auto-loaded on dsh. The iteration flow covers Phase 1 through Phase 5, either interactively or autonomously. The engine enforces deterministic gates, while mstar-* skills remain the source of role and workflow judgement. Supported host adapters listed by the README are dsh, omp, OpenCode, Cursor, Kimi Code, ZCode and Codex.

mstar-harness limitations and access

The engine checks require @mstar-harness/cli on PATH to run; without it, the harness still works but those checks are advisory unless hard enforcement is configured. The package has an installation-script risk and a terminal surface: setup and CLI operations can install components and run commands with the agent’s available permissions. The mstar alias shares its npm bin namespace with an unrelated package, and co-installation can overwrite the shim.

Written from the project's own documentation and kept in sync with it. Where the two disagree, the source is authoritative — read the README on GitHub

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