Scholar Labs Search

by kennethkhoocy

Scholar Labs Search is an Automation skill for Claude Code, published by kennethkhoocy in applied-micro-skills.

48 stars0 forkson kennethkhoocy/applied-micro-skillsAdded 2026/08/11Repository updated 2026/07/22

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applied-microeconomicsclaude-codeclaude-skillscodexcodex-skillsempirical-research

Install in seconds

Install Scholar Labs Search

Copy Scholar Labs Search into your Claude Code skills folder. Run the command in your terminal, or review the source on GitHub before installing.

terminal

npx degit https://github.com/kennethkhoocy/applied-micro-skills/tree/main/plugins/applied-micro/skills/lit-review-orchestrator/scholarlabs-search ~/.claude/skills/scholarlabs-search

Requires Node.js. Downloads this skill only — not the rest of the repository — into your Claude Code skills folder.

Without Node.js

git clone https://github.com/kennethkhoocy/applied-micro-skills.git

Clones the whole repository, then copy the skill’s own directory into your skills folder yourself.

In this catalog

Source file: plugins/applied-micro/skills/lit-review-orchestrator/scholarlabs-search/SKILL.md in kennethkhoocy/applied-micro-skills
Installs to: ~/.claude/skills/scholarlabs-search
Collection: One of 25 skills cataloged from this repository
Category: Automation — 1523 skills

What Scholar Labs Search does

Automates a Google Scholar Labs deep search from a research question, scraping and enriching paper citations via BibTeX export. Used in Stage 2 of a literature review pipeline when explicitly requested.

Scholar Labs Search is cataloged under Automation on DirSkills. Scholar Labs Search comes from a repository tagged applied-microeconomics, claude-code, claude-skills, codex and codex-skills.

Documentation

README

Excerpt

Scholar Labs Search (Stage 2)

Takes the Scholar Labs query that Stage 0 extracts — a single detailed natural-language research question — and returns the papers Google Scholar Labs surfaces, enriched and saved as <stem>.json + <stem>.bib for dedup and screening.

The stage is two halves:

scripts/scholarlabs_search.py — a Playwright driver that signs in, submits the question to Scholar Labs, and reads each result's citation via the standard Scholar Cite → BibTeX export.
scripts/scholarlabs_ingest.py — UI-independent parsing + enrichment. It parses the collected BibTeX, fills missing DOIs (Crossref) and abstracts/journals (OpenAlex), and writes the pipeline JSON. Importable, and runnable standalone on any .bib/.ris file.

Quick start

This is the opening of the README. Read the full README on GitHub.

Frequently asked about Scholar Labs Search

What else does kennethkhoocy publish alongside Scholar Labs Search?
Scholar Labs Search is one of 25 skills that DirSkills catalogs from kennethkhoocy/applied-micro-skills, the repository it ships in. Its siblings there include Adversarial Empirical Review, Annotator Input Parity Check and AsyncOpenAI Concurrency Fix. Each one is a separate skill with its own page in this directory, installs the same way Scholar Labs Search does, and is maintained by kennethkhoocy in that same repository. The rest of the collection is listed on the kennethkhoocy/applied-micro-skills page.
How does Scholar Labs Search compare to other Automation skills?
Scholar Labs Search ranks #1430 by stars among the 1523 Automation skills in this catalog. The most-starred ones next to it are Autonomous Loops, Autonomous Agent Harness and Automation Audit Ops. DirSkills ranks by the star count of the repository each skill ships in, so that order reflects how popular those repositories are rather than any review of Scholar Labs Search against them. Open each page to compare what they document and how they install.