jinze-lee/codex-skills-workbench/keyword-literature-download

Claude Code and agent skill by jinze-lee/codex-skills-workbench

Trust tier 3
  • community
Source check pending

Checking that the SKILL.md file is still in the repository.

Use when the user wants a reusable local workflow to search scholarly APIs for topic keywords, build a candidate table, rapidly download accessible PDFs into a PDF-only folder, optionally cache HTML/XML outside that folder for second-pass PDF discovery, and deduplicate the PDF files.

Install

npx vskill@latest install jinze-lee/codex-skills-workbench/keyword-literature-download

SKILL.md

Keyword Research Harvest

Use this skill when the user gives a topic or keyword set and wants a local literature-harvesting workflow, not a one-off manual search.

What this skill does

  • Bundles its own literature_harvest/scripts stack, including search_pubmed.py, search_europepmc.py, search_crossref.py, search_openalex.py, merge_and_deduplicate.py, download_fulltexts.py, and harvest_utils.py.
  • Searches PubMed/PMC, Europe PMC, Crossref, and OpenAlex through the bundled pipeline.
  • Builds a no-dedup candidate table first.
  • Downloads legal PDFs in parallel for faster collection.
  • Lets the user specify the PDF output folder with --pdf-output-dir or download.pdf_output_dir.
  • Keeps the PDF output folder PDF-only; HTML/XML helper files are cached under download_work/non_pdf_payloads/.
  • Runs a second pass to chase PDF links from saved HTML pages.
  • Produces a PDF-only deduplicated file folder and manifest after downloading.

Dependency model

This skill is self-contained. The target project does not need to already contain:

  • literature_harvest/
  • search_pubmed.py
  • download_fulltexts.py

The bundled copies live under:

  • literature_harvest/scripts/

Files in this skill

  • scripts/run_keyword_harvest_no_dedup.py

Use this to launch a new broad keyword harvest run into a new run folder.

  • scripts/continue_download_and_dedup.py

Use this to resume pending downloads, try HTML-to-PDF second pass, and build a deduplicated download set.

  • literature_harvest/scripts/

Bundled search and download dependencies copied from a working local harvest stack so the skill is portable.

  • references/config_template.json

Copy and edit this for the topic-specific query set and filtering terms.

  • references/prompt_template.md

Reusable prompt for another AI/agent.

Recommended workflow

  1. Choose any output parent folder where the new harvest run folder should be created.
  2. Copy references/config_template.json and edit it for the user's topic keywords.
  3. Run scripts/run_keyword_harvest_no_dedup.py with:
  • --output-root
  • --config
  • --run-name
  • optional --pdf-output-dir <folder> to put generated PDFs in a specific PDF-only folder
  • optional --download-workers <N> to tune parallel downloads
  1. If the job is large, rerun with the same --run-name and --skip-search to avoid repeating API search.
  2. Run scripts/continue_download_and_dedup.py --run-root <run-folder> --retry-failed; it reuses the stored PDF folder unless --pdf-output-dir is supplied again.
  3. Report:
  • candidate count
  • PDF downloaded count
  • true PDF count
  • HTML/XML cache count
  • remaining pending
  • deduplicated keep count

Constraints

  • Do not silently drop failed downloads.
  • Keep metadata even when download fails.
  • Prefer original research when the config asks for it, but do not hard-code one research domain.
  • Do not claim HTML/XML is PDF.
  • Never write HTML, XML, CSV, logs, manifests, or other helper files into the PDF output folder.
  • Verify a file starts with the PDF signature before saving it into the PDF output folder.
  • Treat second-pass cluster-like or support-like annotations as auxiliary only; downloading remains the primary task.

When to read references

  • Read references/config_template.json before preparing a new run config.
  • Read references/prompt_template.md when the user wants to hand this skill to another AI/agent.

Security

  • Security scanPassed, 90 of 100Pattern checks on the skill's files.
  • Model reviewPassed

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

Source

Popularity

Repository stars
78
Repository forks
13
7-day trend score
22

Stars and forks are for the whole GitHub repository, not this skill alone. Refreshed 16 May 2026, 5 months ago.

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