DeepSeek Harness plugin

dsh-agent-arena-leemanch

Isolated multi-model coding matches with deterministic verification, scoring, and reports

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Source facts

Repository
LeemanCheung/dsh-agent-arena
Latest update
Aug 17, 2026
Category
Workflow & Automation
GitHub stars
2
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/LeemanCheung/dsh-agent-arena
Plugin: dsh-agent-arena-leemanch
Author: LeemanCheung

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

dsh-agent-arena

English | 中文

A DSH coding arena for comparing 2–4 configured models in isolated Git worktrees, validating their changes deterministically, reviewing every diff, and explicitly applying one winner.

Screenshot

!Agent Arena results and diff review

> Generated with GPT Image from the implemented Client layout and feature set; runtime appearance follows the active DSH theme and viewport.

Execution and persistence

  • Creates detached worktrees under the operating system temporary directory, outside the compared repository.
  • Starts each contestant with the public ctx.agents.create, SessionId, createUserMessage, and Agent.followup APIs.
  • Executes Git and validation argv through ctx.subprocess.spawn; a shell is never used and shell operators are rejected.
  • Persists match reports through storageDomain. An interrupted nonterminal match is marked failed after Host restart.
  • Polls the generated agentArena Remote namespace in Settings and supports Start, Cancel, diff review, and Apply winner without browser globals.

Scoring and application

Each validation has a positive weight. A contestant score is the percentage of total validation weight that exits successfully; score ties use contestant id as a stable deterministic tie-breaker. No LLM judge is used.

A match requires clean git status --porcelain=v1 before worktrees are created. The winner worktree remains available until explicit application. Apply repeats the cleanliness check, verifies that HEAD still equals the recorded base revision, runs git apply --check, then git apply --index --whitespace=error. Arena never auto-applies, commits, pushes, or rewrites history.

Validation command syntax

The Settings field accepts conservative whitespace-separated argv such as corepack pnpm test or git status --porcelain=v1. Quotes, shell variables, pipes, redirections, command separators, backticks, and newlines are rejected. Configure commands whose arguments do not require shell quoting.

Install

dsh plugin --profile web add github:LeemanCheung/dsh-agent-arena

Restart the existing DSH Web process and refresh its page. The selected profile must provide agents, subprocess, storageDomain, Typert Remotes, Settings, and at least two usable provider/model routes..

Model Experience

Every contestant receives the user-entered Arena objective as one user message in its own session and worktree. Token and KV-cache usage therefore scales with 2–4 independent contestant sessions. Validation, scoring, comparison, cancellation, persistence, and application do not call another model.

Known limitations

Validation argv uses a deliberately conservative tokenizer and cannot represent arguments containing whitespace. Cancellation depends on the selected provider honoring the supplied abort signal. The Host captures binary-capable git diff HEAD, so staged, unstaged, and intent-to-add files are reviewed and applied consistently. Patches over the 1 MB review/apply bound are rejected before mutation rather than truncated.

Development

From the repository root run corepack pnpm typecheck, corepack pnpm test, corepack pnpm build, and corepack pnpm pack:check.

MIT. See [LICENSE](LICENSE).