Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add Felpix-Studios/social-science-research/plugin install social-science-researchWrote 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.
[](https://agentmods.dev/skills/felpix-studios/social-science-research/review-r)<a href="https://agentmods.dev/skills/felpix-studios/social-science-research/review-r"><img src="https://agentmods.dev/badge/skills/felpix-studios/social-science-research/review-r/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.
<a href="https://agentmods.dev/skills/felpix-studios/social-science-research/review-r"><img src="https://agentmods.dev/badge/skills/felpix-studios/social-science-research/review-r.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00043 | $0.00472 |
| Opus 5 | $0.00022 | $0.00236 |
| Sonnet 5 | $0.00009 | $0.00094 |
| Haiku 4.5 | $0.00004 | $0.00047 |
Grade A, and why
review-r 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 12d 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.
What it actually says
Review R Scripts
Run the comprehensive R code review protocol.
Steps
-
Identify scripts to review:
- If
$ARGUMENTSis a specific.Rfilename: review that file only - If
$ARGUMENTSis a name pattern (e.g.,model_name): glob for matching.Rfiles. If multiple matches, use AskUserQuestion:- header: "Scripts"
- question: "Multiple R scripts match that pattern. Which should I review?"
- multiSelect: true
- options: list up to 4 matched files (label: filename, description: path and last modified). User can select multiple.
- If
$ARGUMENTSisall: review all R scripts inscripts/R/andFigures/*/ - If
$ARGUMENTSis empty, glob for all.Rfiles. If multiple found, use AskUserQuestion as above.
- If
-
For each script, launch the
r-revieweragent with instructions to:- Follow the full protocol in the agent instructions
- Read
${CLAUDE_PLUGIN_ROOT}/rules/r-code-conventions.mdfor current standards - Save report to
quality_reports/[script_name]_r_review.md
-
After all reviews complete, present a summary:
- Total issues found per script
- Breakdown by severity (Critical / High / Medium / Low)
- Top 3 most critical issues
-
IMPORTANT: Do NOT edit any R source files. Only produce reports. Fixes are applied after user review.
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.
- 12d ago First seen · 37 lines · 43 tokens per session scan A d7ca2c097445
review-r is a skill published in the GitHub repository Felpix-Studios/social-science-research (8 stars, last pushed 2mo ago), licensed MIT. It adds 43 tokens to every session and 472 once invoked, about $0.0002 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.
Other skills, from other repositories
review-paper-code
Review research code for reproducibility and quality, extract the paper's main empirical claims, compare paper to code, and write a constructive markdown report. Designed for social science / economics projects with LaTeX papers and Stata, R, or Python code.
review-r
Read-only R code review protocol for .R scripts. Checks code quality, reproducibility, domain correctness, tidyverse idioms, and professional standards; produces a report without editing. Use when user says "review this R script", "check the R code", "audit the analysis code", "code review on the R", or when an R file…
aris-experiment-bridge
Code review focused on experiment integrity, not general code quality. Check reproducibility, config-driven design, baseline fairness, seed handling. Triggers: "review experiment code", "check implementation", "bridge review", "is this code reproducible", "audit experiment implementation".
review-asi-contributions
Independently evaluate whether a SlopDotCash/asi contribution delivers a reproducible hill climb, measured research advancement or refutation, or an actual reproduced bug fix. Reject generic improvements, cleanup, and trivial work.
workflows:review
Run multi-agent econometric review on estimation code, identification arguments, and research artifacts.
referee2
Systematic audit and review by Referee 2. Two modes — "deck" reviews slide presentations for rhetoric, visual quality, and compile cleanliness; "code" performs cross-language replication and econometric audit of empirical pipelines. Use when reviewing slides, auditing code, or verifying replication.