dsh-deep-research: An Adaptive Deep-Research Orchestration Plugin for DeepSeek Harness
omdsh-dev/dsh-deep-research
Adaptive deep-research orchestrator plugin for DeepSeek Harness, built on the official workflow engine.
Give DeepSeek Harness an adaptive research loop that plans, researches in parallel, validates marginal gain, and produces cited reports.
dsh plugin --profile web add github:omdsh-dev/dsh-deep-research- Category
- Workflow & Automation
- Platform
- DSH-Plugin
- Author
- omdsh-dev
- Distribution
- Plugin
dsh-deep-research Key Features
dsh-deep-research Repository

dsh-deep-research Repo Summary
dsh-deep-research is a deep-research orchestration plugin (DSH plugin) for DeepSeek Harness, built on the official workflow engine (ctx.workflows / @deepseek-ai/dsh-workflow-workerthread) with a cybernetics and information-theory design. It is not a fixed-prompt pipeline but a living, adaptive research loop. It addresses the problems of blind searching, non-convergence, and hiding uncertainty in traditional research tools. Core capabilities include: a planning agent that defines the answer space and acceptance criteria, research sub-agents that maintain three-state evidence (confirmed/uncertain/gaps), marginal gain validation (stop after one round of zero gain), closed-loop re-planning (auto-dispatch supplementary research), and adversarial review (citation spot-check and coverage audit).
What core features does the dsh-deep-research DSH plugin support?
- Adaptive research loop: Round 1 researches all sub-questions in parallel; after each round, high-priority gaps are collected and automatically dispatched for the next round. Simple topics converge in one round; complex topics expand automatically until marginal gain ≈ 0.
- Information-theory driven: Research sub-agents predict → act (web_search/web_fetch) → update evidence → validate marginal gain; stop after one consecutive round of zero gain, with a hard round limit.
- Coverage self-check: The planning agent enumerates information dimensions, maps each sub-question to a dimension, and outputs coverage_gaps; blind spots are verified by targeted reconnaissance.
- Adversarial review (optional): Citation spot-check (URL reachability/support), coverage audit, contradiction and overconfidence labeling, to counter hallucinations.
- Model tiering: Configurable plannerModel/researcherModel/synthesizerModel/reviewerModel; use strong models for planning/synthesis and cheap models for research, significantly reducing cost.
How to install dsh-deep-research?
Use the following command (replace <profile> with tui / headless / web or your own profile):
dsh plugin --profile <profile> add git+https://github.com/dsh-external/dsh-deep-research.git
dsh --profile <profile>
If pnpm rewrites the https URL to git+ssh (due to a global git insteadof config), use the git+https form above; if dsh plugin prompts for allowBuilds, add a line to $DSH_HOME/profiles/<name>/pnpm-workspace.yaml as instructed.
How to use dsh-deep-research?
The tool is automatically triggered by the model based on its description (deep research/investigation/multi-source information synthesis/research report/literature collection). Just speak naturally in conversation, for example:
- "Deep-dive into the current MCP ecosystem, compare several mainstream implementations, and produce a report with citations."
- "Research according to this question list: 1. ... 2. ..." (if a list exists, skip automatic decomposition and research in parallel)
- "Research A/B options, purpose is to decide which one we choose" (the clearer the purpose, the more accurate the answer space)
Complex topics automatically expand rounds (adaptive loop); simple topics converge in one round. For more rigor, pass depth: 3; for citation correction and coverage audit, pass review: true.
What DeepSeek Harness components does dsh-deep-research depend on?
The profile combination must include the official workflow engine and built-in web tools—the official dsh base combination includes them, no extra installation needed; peer dependencies (like @deepseek-ai/dsh-tools) are provided by the combination, and setting autoInstallPeers: false in the profile avoids looking up unpublished @deepseek-ai/* packages from the registry.
How to update and uninstall dsh-deep-research?
dsh plugin --profile <profile> update
dsh plugin --profile <profile> remove @dsh-external/dsh-deep-research
# Or: remove the dependency from the profile's package.json and then run dsh plugin --profile <profile> update
This plugin is maintained by omdsh-dev, licensed under MIT, last updated in 2026-08. The source is the runtime (the package entry points directly to src/index.ts, no build step), and it requires erasable-only TS syntax.