dsh-research

AI4Scholar Research Pack for DeepSeek Harness

English | 中文

The orchestration layer that turns DeepSeek Harness into a research workbench. It searches nothing itself: it ships the research skills, the literature-first workflow guidance, and the workspace conventions that make capability plugins (dsh-ai4scholar) and the agent behave like one research assistant.

What it installs

Four research skills (authored by AI4Scholar, embedded in the package — nothing to download):

Skill	When the agent loads it
ai4scholar-paper-review	Pre-submission review from five reviewer perspectives, with a fix-priority list
ai4scholar-introduction-writing	Introductions: background → gap → contribution → signposting → polish
ai4scholar-academic-formatting	Reference formatting, three-line tables, abstract structure, re-submission reformatting
ai4scholar-reference-audit	Reference audit: cross-citation, format consistency, DOI checks, duplicates, self-citation

One workflow section in the system prompt: search before asserting, which task loads which skill, and a workspace layout — papers in papers/, citations in references.bib, reading notes in notes/ — so the next session can pick up where the last one stopped.

What the agent does with it

A request like "find the strongest recent evidence for X, then draft an introduction around it" runs as one chain instead of four disconnected answers:

1. The guidance forbids answering from memory, so the agent calls search_papers first and works from what came back.
2. It reads the full text of the papers that matter with the read_* tools, and files them under papers/ with one note each in notes/.
3. ai4scholar-introduction-writing loads before any prose is written, so the draft follows background → gap → contribution → signposting rather than improvised paragraphs.
4. Every work it cites lands in references.bib, and ai4scholar-reference-audit can check that list against the text before submission.

The next session starts from those three files, so the work accumulates instead of restarting.

How it adapts

The guidance is rebuilt at every prompt assembly, so it states what is actually available right now:

Composition	What the pack contributes
dsh-research + dsh-ai4scholar	Skills, plus a workflow that routes the model to the literature tools by name
dsh-research alone	Skills, plus a workflow that tells the user how to install the literature tools before relying on any citation
A profile without a skill registry	The workflow only. It stops advertising the skills rather than sending the model after a loader that cannot resolve them

Install

dsh plugin --profile web add dsh-ai4scholar dsh-research
dsh web

One command, two independent layers: dsh-ai4scholar brings 38 literature tools (Semantic Scholar / PubMed / Google Scholar / arXiv / bioRxiv / DOI full text / auto-cite / figures), this pack brings the skills and the workflow. The pack works alone too — the skills still load, there is just nothing to search with.

Configuration

The bundle inserts one row (id: research-pack). Override it from your profile's cordis.patch.yml (a patch replaces the whole config, so restate every key you keep):

- id: research-pack
  config:
    skills: true                  # register the bundled skills
    skillNames: []                # register only these; empty means all
    promptGuidance: true          # register the workflow section
    promptOrder: 140
    workspaceConventions: true    # state the workspace layout in the guidance
    papersDir: papers/
    bibliographyFile: references.bib
    notesDir: notes/
    language: zh                  # zh | en — guidance and skill catalog copy

Language

language selects the language of the workflow section and of each skill's catalog entry. The skill bodies stay Chinese in both settings — they are AI4Scholar's originals, kept verbatim so they stay in sync with their published source. Under language: en the guidance says so explicitly and tells the model to carry the procedure out but report back in the language the user is writing in.

Notes

• Skill bodies are the ones published on ai4scholar.net, embedded through ctx.skills.register — no directories to configure, and written in Chinese (see Language).
• This pack is an orchestration layer, not a container: member plugins install beside it and keep their own settings pages, cards, and release cadence.
• Skill content is MIT licensed; use and adapt freely.

License

MIT