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How to find papers on Crossref and triage them as candidates with Research Workbench Assistant

Search Crossref by topic and year, save deduplicated candidates, and record keep or exclude reasons.

Short answer: Create a workbench to search in with python -X utf8 skills/research-workbench/scripts/workbench.py init --root demo-workbench --name "示例科研项目"; then run python -X utf8 skills/research-workbench/scripts/workbench.py discover --root demo-workbench --query "renewable energy forecasting" --year-start 2023 --year-end 2025 --limit 10 to query Crossref and save results. All steps.

  • Research
  • Intermediate
  • 30 minutes
  • From the README
  • Any agent

Who it is forA researcher starting a literature review on a new topic who needs a shortlist of papers to screen, without marking them as read.

The problemLiterature searches produce many results, and it is easy to confuse a search hit with a paper that was actually read.

The outcomeA candidate queue in CANDIDATES.md and JSON with deduplicated DOIs and search batch records. Candidates stay separate from read notes until you write a note for the same DOI.

What you need first

  • A working local Codex installation with an account that can use it
  • Python 3.10 or newer
  • Git

Steps

  1. Create a workbench to search in with python -X utf8 skills/research-workbench/scripts/workbench.py init --root demo-workbench --name "示例科研项目".
  2. Run python -X utf8 skills/research-workbench/scripts/workbench.py discover --root demo-workbench --query "renewable energy forecasting" --year-start 2023 --year-end 2025 --limit 10 to query Crossref and save results.
  3. Run python -X utf8 skills/research-workbench/scripts/workbench.py candidates --root demo-workbench to list the queue as pending, kept, or excluded.
  4. Open CANDIDATES.md in the workbench, then write a reason for each keep or exclude decision. Do not mark a candidate as read unless you have actually read it.

Prompt for your agent

In the research-workbench-assistant repo, run the discover command against the workbench at <workbench-path> with the query <topic> for years 2023 to 2025 and a limit of 10. Expected output: CANDIDATES.md and CANDIDATES.json with pending entries. Verify that no candidate is marked as read.

Caveat. Crossref does not cover every paper, the query returns at most 50 results by relevance, and the search terms are sent to Crossref, so avoid unpublished research details in queries.

Use this in your AI agent

Ask your agent

Using the Deduped MCP, get the setup steps for z-liu-xiugou/research-workbench-assistant and "Find papers on Crossref and triage them as candidates"

Add Deduped to Claude Code once

claude mcp add --transport http deduped https://dedupedai.com/mcp

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