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AutomationPython

Lit Review Orchestrator

by kennethkhoocy

Lit Review Orchestrator 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
applied-microeconomicsclaude-codeclaude-skillscodexcodex-skillsempirical-research
Install in seconds
Install Lit Review Orchestrator
Copy Lit Review Orchestrator 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 ~/.claude/skills/lit-review-orchestrator

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/SKILL.md in kennethkhoocy/applied-micro-skills
Installs to
~/.claude/skills/lit-review-orchestrator
Collection
One of 25 skills cataloged from this repository
Category
Automation1523 skills

What Lit Review Orchestrator does

Orchestrates a multi-source literature search pipeline from a document. Give it a .tex or .docx describing an article, extracts a search plan, runs Undermind and Google Scholar searches, then merges, deduplicates, and screens results.

Lit Review Orchestrator is cataloged under Automation on DirSkills. Lit Review Orchestrator comes from a repository tagged applied-microeconomics, claude-code, claude-skills, codex and codex-skills.

Documentation

README

Lit-Review Orchestrator

Run the literature-review pipeline from a single command, starting from a document that describes your article.

Input: a .tex or .docx document — a full manuscript, an abstract, or any text describing the article's content. Output: a deduplicated, relevance-screened master list (JSON + RIS), plus the extracted search plan and all intermediate stage files.

Quick Start

The orchestrator.py commands below are the autonomous fallback (reasoning on the Sonnet/DeepSeek API). When an agent runs this skill interactively, use the agent-driven flow instead; see How it runs below. That flow performs non-browser reasoning at the agent layer with no Anthropic API key, using the platform routing in docs/claude-code.md or docs/codex.md.

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

Frequently asked about Lit Review Orchestrator

  • What else does kennethkhoocy publish alongside Lit Review Orchestrator?

    Lit Review Orchestrator 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 Lit Review Orchestrator 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 Lit Review Orchestrator compare to other Automation skills?

    Lit Review Orchestrator ranks #1427 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 Lit Review Orchestrator against them. Open each page to compare what they document and how they install.

More from kennethkhoocy/applied-micro-skills

Lit Review Orchestrator is one of 25 skills cataloged on DirSkills from kennethkhoocy/applied-micro-skills.

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3w ago

Adversarial Empirical Review

Automates verification that empirical research tables are correct by comparing them against the underlying data and analysis code through an adversarial, regression-gated review pipeline. Use when you need to audit whether numbers in LaTeX tables match computed results.
Quality
480
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3w ago

Annotator Input Parity Check

Audit the annotation protocol to ensure the model receives the same input as human annotators, preventing recall ceilings and misdiagnosed failures. Use before designing any label-replication model, or when a validation report shows low recall on label subsets.
AI Engineering
480
🚀
3w ago

AsyncOpenAI Concurrency Fix

Fixes a silent throughput ceiling in asyncio LLM batch pipelines by overriding the default httpx connection pool limit to match the desired concurrency. Use when raising the asyncio semaphore above ~100 produces no gain.
AI Engineering
480
✍️
3w ago

Cite Placement

Unified router for placing pre-screened citations into manuscripts or restyling existing citations. Supports inline, footnote placement, and full style conversion for LaTeX and Word documents.
Writing
480
🔍
3w ago

DeepResearch Search

Runs a deep literature search using Google Gemini's Deep Research agent via API, parses the cited report into structured data for a literature review pipeline. Use only when explicitly requested as an API-driven alternative to browser-based deep searches.
Automation
480
📄
3w ago

Download Gated PDFs

Downloads the actual PDF from bot-gated websites (e.g., taxpolicycenter.org, SSRN mirrors) that return HTML instead of PDFs. Uses the Wayback Machine's raw-content (id_) URL to obtain the original binary, bypassing bot challenges.
Automation
480