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.
git clone --depth 1 https://github.com/brycewang-stanford/Auto-Empirical-Research-SkillsWrote 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/agents/brycewang-stanford/auto-empirical-research-skills/r-reviewer)<a href="https://agentmods.dev/agents/brycewang-stanford/auto-empirical-research-skills/r-reviewer"><img src="https://agentmods.dev/badge/agents/brycewang-stanford/auto-empirical-research-skills/r-reviewer/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/agents/brycewang-stanford/auto-empirical-research-skills/r-reviewer"><img src="https://agentmods.dev/badge/agents/brycewang-stanford/auto-empirical-research-skills/r-reviewer.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 | $0.00034 | $0.01675 |
| Opus 5 | $0.00017 | $0.00838 |
| Sonnet 5 | $0.00007 | $0.00335 |
| Haiku 4.5 | $0.00003 | $0.00168 |
Grade A, and why
r-reviewer 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 9d 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.
The source is not reproduced here
A licence we could not identify
The repository carries a LICENSE file, but it is custom or dual enough that GitHub cannot name it and neither can this catalogue. Unknown terms are not permission, so the body is not copied here. Read the licence at the source and decide for yourself.
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.
- 9d ago First seen · 174 lines · 34 tokens per session scan A df38b256e138
r-reviewer is an agent published in the GitHub repository brycewang-stanford/Auto-Empirical-Research-Skills (3,759 stars, last pushed 5d ago), with no licence file. It adds 34 tokens to every session and 1,675 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 2026-09-03.
Other agents, from other repositories
r-reviewer
R code reviewer for academic scripts. Checks code quality, reproducibility, figure generation patterns, and theme compliance. Use after writing or modifying R scripts.
sim-reviewer
Monte Carlo simulation reviewer. Checks the parts of a simulation study that general R review misses — the assumption regime a run is in, DGP/estimand alignment, replication budget and Monte Carlo standard error, coverage computed against the truth, parallel-seed discipline, and whether headline simulation claims…
code-review
Multi-persona orchestrator for adversarial review of R, Python, Julia, or Stata research scripts. Runs an 11-category baseline checklist, then dispatches 3-6 specialist sub-agents (correctness, reproducibility, design, plus optional domain / performance / security) in parallel. Deduplicates findings across reviewers…
agent-tufte-designer
Output synthesizer. Takes Statistician + Critic output and formats it in dense Tufte-style markdown. Zero prose fluff, maximum data density, self-explanatory tables, narrative margin notes. The ONLY agent whose output the user sees.
structure_architect_agent
Designs the papers section architecture and detailed outline before drafting begins.
formatter_agent
Formats the final manuscript output to target journal style requirements.