literature-review

literature-review is a skill for Claude Code from agentlas-ai/agentlas-desktop. It costs 86 tokens per session (2,955 once invoked), scanned C, a copy of literature-review, Apache-2.0.

A process for finding, checking, and synthesizing academic research across sources such as PubMed, arXiv, bioRxiv, and Semantic Scholar. bioRxiv is a repository for scientific papers shared before formal journal review.

In plain words
What is it for?
Use it for systematic or scoping reviews, meta-analyses, research synthesis, literature searches, identifying research gaps, and writing review sections for papers or theses.
Why use it?
It reduces missed studies, unreliable citations, and unsupported summaries when reviewing a large body of research.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: built for openclaw.

Good fit Use it for systematic or scoping reviews, meta-analyses, research synthesis, literature searches, identifying research gaps, and writing review sections for papers or theses.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/agentlas-ai/agentlas-desktop/literature-review
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add agentlas-ai/agentlas-desktop --skill literature-review
Clone the repo
git clone --depth 1 https://github.com/agentlas-ai/agentlas-desktop

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for literature-review

README.md
[![agentmods](https://agentmods.dev/badge/skills/agentlas-ai/agentlas-desktop/literature-review/github.svg)](https://agentmods.dev/skills/agentlas-ai/agentlas-desktop/literature-review)
Your own site
<a href="https://agentmods.dev/skills/agentlas-ai/agentlas-desktop/literature-review"><img src="https://agentmods.dev/badge/skills/agentlas-ai/agentlas-desktop/literature-review/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for literature-review

Your own site · 80×15
<a href="https://agentmods.dev/skills/agentlas-ai/agentlas-desktop/literature-review"><img src="https://agentmods.dev/badge/skills/agentlas-ai/agentlas-desktop/literature-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 86 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,955 The whole file, excluding the scripts and references it only reads on demand.
Security scan C 2 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 100% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00086 $0.02955
Opus 5.5 $0.00034 $0.01182
Sonnet 5.5 $0.00017 $0.00591
Haiku 4.5 $0.00009 $0.00296

Measured 1mo ago against content hash 950a6d0863ef, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade C, and why

literature-review scanned grade C with 2 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.

The scan reads SKILL.md. This mod also ships 5 executable files (scripts/generate_pdf.py, scripts/generate_schematic_ai.py, scripts/generate_schematic.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Downloads and executes remote codehighSupply chain

curl | sh runs whatever the server returns today, which is not necessarily what it returned when this was reviewed.

curl -fsSL https://parallel.ai/install.sh | bash

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

curl -fsSL https://parallel.ai/install.sh | bash
Origin

This is a copy

100% identical to literature-review — 153 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

plugins/agentlas-science-skills/skills/literature-review/SKILL.md · 281 lines

How it starts

The opening of the file, as written. The whole thing — 281 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Literature Review

Overview

Conduct systematic, comprehensive literature reviews following rigorous academic methodology. Search multiple literature databases, synthesize findings thematically, verify all citations for accuracy, and generate professional output documents in markdown and PDF formats.

This skill uses the parallel-web skill (parallel-cli search) as the primary web search tool for broad academic literature discovery, supplemented by specialized database access skills (gget, bioservices, datacommons-client). It provides specialized tools for citation verification, result aggregation, and document generation.

When to Use This Skill

Use this skill when:

  • Conducting a systematic literature review for research or publication
  • Synthesizing current knowledge on a specific topic across multiple sources
  • Performing meta-analysis or scoping reviews
  • Writing the literature review section of a research paper or thesis
  • Investigating the state of the art in a research domain
  • Identifying research gaps and future directions
  • Requiring verified citations and professional formatting

Visual Enhancement with Scientific Schematics

⚠️ MANDATORY: Every literature review MUST include at least 1-2 AI-generated figures using the scientific-schematics skill.

This is not optional. Literature reviews without visual elements are incomplete. Before finalizing any document:

  1. Generate at minimum ONE schematic or diagram (e.g., PRISMA flow diagram for systematic reviews)
  2. Prefer 2-3 figures for comprehensive reviews (search strategy flowchart, thematic synthesis diagram, conceptual framework)

How to generate figures:

  • Use the scientific-schematics skill to generate AI-powered publication-quality diagrams
  • Simply describe your desired diagram in natural language
  • Nano Banana Pro will automatically generate, review, and refine the schematic

How to generate schematics:

python scripts/generate_schematic.py "your diagram description" -o figures/output.png

Read the full file on GitHub · 281 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 1mo ago First seen · 281 lines · 86 tokens per session scan C 950a6d0863ef

Subscribe to this mod's changes

literature-review is a skill published in the GitHub repository agentlas-ai/agentlas-desktop (6 stars, last pushed yesterday), licensed Apache-2.0. It adds 86 tokens to every session and 2,955 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it C with 2 findings (downloads and executes remote code, makes network calls). It is 100% identical to literature-review, differing in 153 lines, and is treated as a copy.

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