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/domain-referee)<a href="https://agentmods.dev/agents/brycewang-stanford/auto-empirical-research-skills/domain-referee"><img src="https://agentmods.dev/badge/agents/brycewang-stanford/auto-empirical-research-skills/domain-referee/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/domain-referee"><img src="https://agentmods.dev/badge/agents/brycewang-stanford/auto-empirical-research-skills/domain-referee.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 | $0.00052 | $0.01396 |
| Opus 5 | $0.00026 | $0.00698 |
| Sonnet 5 | $0.00010 | $0.00279 |
| Haiku 4.5 | $0.00005 | $0.00140 |
Grade A, and why
domain-referee 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 8d 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.
- 8d ago First seen · 148 lines · 52 tokens per session scan A 1093d6510b7c
domain-referee is an agent published in the GitHub repository brycewang-stanford/Auto-Empirical-Research-Skills (3,745 stars, last pushed 4d ago), with no licence file. It adds 52 tokens to every session and 1,396 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 2026-09-03.
Other agents, from other repositories
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…
fatal-error-check
Fast pre-review check for fatal errors in LaTeX papers. Launch BEFORE full review agents (paper-critic, domain-reviewer, referee2-reviewer). Binary PASS/FAIL verdict in 15-30 seconds. Checks compilation, placeholders, broken references, number contradictions, and section completeness. Examples: Example 1: user: "Quick…
formatter_agent
Formats the final manuscript output to target journal style requirements.
intake_agent
Conducts the paper configuration interview and produces the Paper Configuration Record for downstream agents.
stata-analyst
End-to-end statistical analysis agent for Stata. Handles the full workflow from data loading through estimation, results retrieval, and graph export. Invoke when user wants a complete analysis, asks to "run a regression", "analyze this dataset", or describes a multi-step econometric workflow.
stata-replication-lead
Specialist agent for replication, robustness, and multi-specification evidence gathering in Stata. Invoke when the user needs a paper result reproduced, a pipeline rerun, or a structured robustness campaign.