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Research Refs — DeepSeek Harness 插件(DSH Plugin)
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dsh-research-refs

Research Refs

DSH 插件:将杂乱粘贴的引文整理为格式统一的参考文献(refs_parse → refs_verify → refs_dedup → refs_format + research-refs skill)

插件会安装到这里;不确定时保持 web。

npx -y @deepseek-ai/dsh plugin --profile web add github:Parker-xia/dsh-research-refs#ae39d0f3dcef3ee5c5ac8e75b648f65b8484da72
README兼容性版本

兼容性与来源证明

Research Refs 以 dsh-research-refs 发布,当前版本为 0.2.0。Plugin Hub 会校验它的 manifest,并保存精确安装来源,便于复现安装结果。

DSH 兼容范围
*
运行环境
any
发布来源
github
Registry 更新时间
2026/8/26

版本

0.2.0stable
2026/8/26

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最新版
0.2.0
DSH
*
HMR
重启进程
Tree shaking
未声明可安全裁剪
解包体积
未提供
文件数
未提供
Surface
any
许可证
MIT
发布源
github
GitHub
★ 0
周下载
0
最近提交
2026/8/26
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README

dsh-research-refs

A DeepSeek Harness (DSH) plugin that turns messy pasted citations into uniformly formatted references. Derived from the opencode research-refs skill and rebuilt as a deterministic tool chain — parsing, verification, deduplication and formatting are done by code, while the skill only orchestrates the flow.

Features

Four tools plus one orchestration skill:

ToolPurpose
refs_parseSplit messy citation text into individual entries (numbering → blank lines → type-marker strategies), best-effort field parsing; entries with missing fields or uncertain splits carry flags
refs_verifyVerify and complete via Crossref: with a DOI, query works/{DOI} to fill volume/issue/pages, journal and year; without a DOI, search by title + authors (similarity ≥ 0.9 auto-applied, otherwise the top 5 candidates are returned for the user to choose). Chinese references are marked "not verifiable online"
refs_dedupAutomatic deduplication: identical DOI, or title similarity ≥ 0.85 with the same first-author surname; keeps the most complete / already-verified entry and reports what was removed
refs_formatOutput in GB/T 7714-2015 / APA / Vancouver; English authors normalized to "SURNAME Initials" (e.g. ZHANG S), Chinese authors keep their full names; ends with a pending-items list; optionally writes a .md file

The research-refs skill teaches the model to orchestrate the pipeline as "parse → confirm with the user → verify (candidate selection) → dedup → ask for style → output", and enforces the iron rules: never fabricate fields — anything unverifiable is marked pending.

Install

npm i github:Parker-xia/dsh-research-refs

Add to your composition

Append to your DSH composition (cordis.yml or an agent preset's agent.cordis.yml):

- id: research-refs
  name: 'dsh-research-refs'

Or use the bundle patch mechanism (dsh bundle patch, see cordis.patch.yml).

Tested against @deepseek-ai/dsh@0.1.0-rc.6 — the preview moves fast, so pin this version or check GitHub Discussions when upgrading. Requires the host tools service; fs / skills are optional (the capability degrades gracefully and is flagged when missing).

Online verification is self-sufficient: refs_verify uses Node's native fetch (always present on DSH's Node ≥ 22 engine) to talk to Crossref directly — it does not require the host to configure any web fetch provider, and it does not register one (so it can never conflict with a host provider). If native fetch is unavailable (e.g. inside the dynamic sandbox), it automatically falls back to the ctx.web service.

Usage

Paste a messy block of citations and say something like "clean up these references". The agent loads the skill and reports at every step of the pipeline:

You: clean up these references:
    1. Zhang S et al. 2021. Deep learning for CT reconstruction...
    2. Wang S (2024) Image reconstruction algorithms...

Agent: [refs_parse] 2 entries split, all fields recognized...
       [refs_verify] #1 verified (DOI), #2 candidates awaiting choice...
       [refs_dedup] 2 kept, none removed
       [refs_format] GB/T 7714-2015 output...

License

MIT