DeepSeek Harness plugin

dsh-moa-morphlin

Mixture of Agents (MoA) tool plugin for DeepSeek Harness — run several models in parallel on the same prompt, then have a stronger aggregator model synthesize a final answer. On-demand tool, zero

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Source facts

Repository
morphlinglan/dsh-moa
Latest update
Aug 16, 2026
Category
Tools & Capabilities
GitHub stars
0
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/morphlinglan/dsh-moa
Plugin: dsh-moa-morphlin
Author: morphlinglan

Check the source files

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

File explorer2 files
README.mdSource · read only

dsh-moa

A DeepSeek Harness plugin that adds Mixture of Agents (MoA) as an on-demand tool: run_moa.

Instead of using one model, MoA sends the same prompt to several proposer models in parallel, then has a stronger aggregator model synthesize the best final answer from all their outputs. It is not on the normal request path — the agent calls the tool only when multi-model synthesis is worth the extra tokens/latency.

Install

dsh plugin --profile web add github:morphlinglan/dsh-moa

Then restart dsh web if it is already running.

Usage

Configure the proposer pool and aggregator in your profile's cordis.patch.yml:

- insert:
    - id: dsh-moa
      name: dsh-moa
      config:
        toolName: run_moa
        # Replace with your own providers/models.
        proposers:
          - provider: proposer-provider-a
            model: proposer-model-a
          - provider: proposer-provider-b
            model: proposer-model-b
        aggregator:
          provider: aggregator-provider
          model: aggregator-model
        minProposers: 2
        proposerMaxTokens: 1500
        aggregatorMaxTokens: 2500
        fallbackLongest: true
        maxRetries: 2

The providers/models above are placeholders only. Replace them with providers and models you actually have access to.

Then ask the agent to use run_moa for complex analysis, synthesis, translation, or review tasks.

Config

FieldTypeDefaultDescription
toolNamestring"run_moa"Tool name registered in DSH.
proposers{ provider, model }[][]Models that independently answer the prompt in parallel.
aggregator{ provider, model }requiredStronger model that synthesizes the final answer.
minProposersnumber2Minimum successful proposers required to run aggregation.
proposerMaxTokensnumber1500Output cap for each proposer.
aggregatorMaxTokensnumber2500Output cap for the aggregator.
fallbackLongestbooleantrueIf the aggregator fails, fall back to the longest proposer output.
temperaturenumberOptional sampling temperature passed to every call.
reasoningEffortstringOptional adapter-owned reasoning effort id.
maxRetriesnumber0Retries per proposer/aggregator on transient errors, with exponential backoff.
iterationsnumber1Iterative MoA rounds (1 = single layer + aggregator).

License

MIT