dsh-super-code

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A smarter, leaner, faster, and easier-to-use coding plugin for DeepSeek Harness.

On SWE-bench Pro hard-100, compared with the official Standard preset (same host DSH 0.2.1-rc.2, same model, both on high reasoning effort and legacy budgets):

Tested on version 0.3.5. Full results and limitations

Install

Supports Harness from 0.1.5-alpha.1, with Web verified through 0.2.1-rc.4; see compatibility for tested desktop versions.

Desktop: open Plugins → Add plugin in the left sidebar, enter dsh-super-code, then click Install and Enable now (on older versions, reload or restart when prompted). Desktop includes its own runtime; Node.js is not required.

Web / CLI: requires Node.js 22 or later.

npm install -g @deepseek-ai/dsh            # skip if dsh is already installed
dsh plugin --profile web add dsh-super-code

Download the .tgz file from GitHub Releases.

Desktop: enter the full path of the package in "Package name or address", then click Install.

Web: run the following command (use the actual file name):

dsh plugin --profile web add ./dsh-super-code-0.3.9.tgz

Usage

1. Open Settings → Agent Presets and select Super Code (identifier super-code).
2. Create a new session and describe the task.

Model, reasoning effort, permissions, and tools follow the Harness settings and need no separate configuration. Child Agents use the parent Agent's model by default.

If the preset is not listed, check its status in Settings → Super Code, or see troubleshooting.

Select Super Code in the right sidebar. It contains three sections:

• Tasks: goal, step progress, tool-call summaries, and changed files. Read-only.
• Collaborative execution: the Agent execution tree. Click a node to view details.
• Memory: view, add, edit, and delete project memory and global preferences.

The three sections open one at a time. Tasks opens by default; click the current heading to collapse it.

Screenshots use the current UI with sample data to illustrate the plugin.

Features

See the usage guide.

Recent releases

• 0.3.9: Polished Settings and the task sidebar, improved MCP conversation control, fixed PTC child-tool approvals, and verified rc.4 Web compatibility.
• 0.3.8: Added MCP connection; external clients can delegate, inspect, continue, and cancel DSH conversations. Added a Home overview in Settings.
• 0.3.7: Added three-level deletion protection (Relaxed by default). Added Task status to the sidebar.

Full changelog

Versions follow major.performance.maintenance: a change in the second number indicates improved coding results or efficiency; the third covers fixes, UI, and compatibility. Every release requires extensive regression testing, so the release cycle may be long.

Evaluation

Method

• Task set: SWE-bench Pro hard-100, graded with the official grader. Tuning uses only 33 hard tasks selected from the SWE-bench dev split; hard-100 is used only to evaluate frozen candidates and investigate issues, never for tuning, to avoid overfitting to the evaluation tasks.
• Baseline: the official Standard preset rather than Minimal. On the old host, Standard + high passed 51 tasks and Minimal + high passed 46, with Standard using 23.5% fewer tokens per task. Comparing against the stronger baseline gives a stricter conclusion.
• Controlled variables: same host, model, reasoning effort, and budgets; only the Agent preset differs.
• Metrics: tasks passed, net time per task (excluding failed requests and retry waits), tokens per task, and model calls per task.

Process

1. Old-host baseline (DSH 0.1.5-rc.2, deepseek-v4.1-flash, high): the Super Code 0.3.0 candidate passed 56 tasks, the official Standard preset 51, and Minimal 46. Relative to Minimal, time fell by 47.6% and tokens by 44.9%.
2. Regression after the host upgrade: after upgrading to DSH 0.2.1-rc.2 and deepseek-v4.1-flash-1017, under default budgets Standard dropped to 46 and Super Code 0.3.4 to 41, below Standard. Investigation found the new host had tightened context budgets: the compression threshold fell from 800,000 to 550,464 tokens, and retained verbatim context from 160,000 to 98,560 tokens.
3. Retest with legacy budgets: both sides used legacy budgets. Standard stayed at 46 with 14.2% more tokens; Super Code 0.3.5 rose to 49 with only 0.4% more tokens and 19.4% less net time. Based on this, the plugin uses legacy budgets by default from 0.3.6.
4. Cross-model check (glm-5.3-flash, max): Super Code 0.3.4 passed 45 tasks and native ZCode 29. Super Code used less net time per task (32.9 vs 52.3 min) and more tokens (5.50 M vs 3.61 M).

Summary

Limitations

• Each configuration was run once. The same task can pass in one run and fail in another; run-to-run variance for a fixed configuration has not been estimated.
• The default-budget and legacy-budget runs used different plugin versions (0.3.4 → 0.3.5), so the gain cannot be attributed entirely to budgets.
• 0.3.6 – 0.3.9 have not been re-evaluated on the 100 tasks.
• The cross-model comparison is between two complete systems and cannot isolate the plugin's contribution.

Results and methodology · All result tables

Acknowledgements

This project recognizes the LINUX DO community.

Detailed acknowledgements and licenses · This project is licensed under Apache-2.0.