lit-review

lit-review is a skill for Claude Code from Felpix-Studios/social-science-research. It costs 53 tokens per session (1,914 once invoked), scanned A, original, MIT.

A structured literature-review workflow that uses several research agents to survey existing academic work. It searches journals and working-paper repositories such as NBER, SSRN and IZA, then follows citation links from important papers.

In plain words
What is it for?
Use it to review research on a question or topic, especially when you already know one to three important papers. It is for surveying literature, not for finding datasets or writing a paper.
Why use it?
It reduces the time spent finding relevant research and tracing how papers connect. It also checks the project's existing papers, bibliography and field information before searching.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: names the AskUserQuestion tool.

Part of the social-science-research plugin — 13 skills, 9 agents, 3 hooks shipped together

Good fit Use it to review research on a question or topic, especially when you already know one to three important papers. It is for surveying literature, not for finding datasets or writing a paper.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/felpix-studios/social-science-research/lit-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 Felpix-Studios/social-science-research --skill lit-review
Clone the repo
git clone --depth 1 https://github.com/Felpix-Studios/social-science-research

Made for: Claude Code.

Or install social-science-research, the plugin that ships this one along with the rest of its 13 skills, 9 agents, 3 hooks.

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 lit-review

README.md
[![agentmods](https://agentmods.dev/badge/skills/felpix-studios/social-science-research/lit-review/github.svg)](https://agentmods.dev/skills/felpix-studios/social-science-research/lit-review)
Your own site
<a href="https://agentmods.dev/skills/felpix-studios/social-science-research/lit-review"><img src="https://agentmods.dev/badge/skills/felpix-studios/social-science-research/lit-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 lit-review

Your own site · 80×15
<a href="https://agentmods.dev/skills/felpix-studios/social-science-research/lit-review"><img src="https://agentmods.dev/badge/skills/felpix-studios/social-science-research/lit-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 53 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,914 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found 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 $0.00053 $0.01914
Opus 5 $0.00026 $0.00957
Sonnet 5 $0.00011 $0.00383
Haiku 4.5 $0.00005 $0.00191

Measured 11d ago against content hash 4425623ebc22, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

lit-review scanned grade A with 0 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 11d ago.

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.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/lit-review/SKILL.md · 200 lines

How it starts

The opening of the file, as written. The whole thing — 200 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Literature Review

Conduct a systematic literature review using a parallel fleet of Librarian agents, each searching a different angle. Citation chains from anchor papers are the highest-yield search vector and always run when anchor papers are available.

Input: $ARGUMENTS — a topic, research question, or the title of a known key paper.

Step 1: Orient and Gather Context

  1. Read quality_reports/project_spec_*.md or quality_reports/research_*.md if they exist — extract the research question and identification strategy.
  2. Check references/papers/ — list any PDFs already on hand.
  3. Read the project .bib file (Bibliography_base.bib or any .bib at project root) — extract paper titles and authors already known.
  4. Read references/domain-profile.md if it exists — get the field's journal list and key researchers.
  5. Identify anchor papers: the 1–3 most central known papers (from existing bib or supporting docs). These seed the citation chain search.

If references/domain-profile.md does not exist, use AskUserQuestion to determine the field:

  • header: "Field"
  • question: "What field is this research in? This determines which journals and repositories the librarian agents search."
  • options:
    • label: "Economics", description: "AER, QJE, Econometrica, JPE, ReStud + NBER/IZA"
    • label: "Political Science", description: "APSR, AJPS, JOP, CPS, World Politics"
    • label: "Sociology", description: "ASR, AJS, Social Forces, Demography"
    • label: "Public Health", description: "NEJM, Lancet, JAMA, AJE"

Step 2: Assign Librarians

Dispatch 3–5 Librarian agents in parallel using Task. Each gets a specific search angle, the topic, and the anchor papers (if any).

Always dispatch (3 minimum):

Librarian 1 — Top Journals:

Task prompt: "You are a Librarian agent. Topic: [topic]. Search angle: Top Journals.
Field: [field from domain-profile or user answer].
Top journals to search: [list from domain-profile, or infer for field].
Anchor papers (for context only): [list].
Find the 8-12 most relevant published papers from the past 10 years.
For seminal papers, go back further. Follow the Librarian agent instructions."

Read the full file on GitHub · 200 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. 11d ago First seen · 200 lines · 53 tokens per session scan A 4425623ebc22

Subscribe to this mod's changes

lit-review is a skill published in the GitHub repository Felpix-Studios/social-science-research (8 stars, last pushed 2mo ago), licensed MIT. It adds 53 tokens to every session and 1,914 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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