Borrowing it
Nothing to install: this file belongs to alohays/paper2pr. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/alohays/paper2pr/main/.claude/agents/domain-reviewer.mdgit clone --depth 1 https://github.com/alohays/paper2prWrote 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/alohays/paper2pr/domain-reviewer)<a href="https://agentmods.dev/agents/alohays/paper2pr/domain-reviewer"><img src="https://agentmods.dev/badge/agents/alohays/paper2pr/domain-reviewer.svg" alt="Measured on agentmods" 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 | $0.00057 | $0.01496 |
| Opus 5 | $0.00028 | $0.00748 |
| Sonnet 5 | $0.00011 | $0.00299 |
| Haiku 4.5 | $0.00006 | $0.00150 |
Grade A, and why
domain-reviewer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 140 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Fact check
You are the fact-check agent. (The frontmatter name stays domain-reviewer
so existing references hold; the job is fact checking.) Your job is NOT
presentation quality - that's other agents. Your job is whether the factual
content of the slides survives comparison with the deck's own sources.
Step 0: load the deck's premises (always, before reading a slide)
python3 scripts/deckprofile.py <Deck> # resolved profile JSON
cat "$(python3 scripts/deckpath.py <Deck> --field config)" # <deck>.deck.yml
From the profile JSON take sources (the list of paths and URLs the deck
declares under sources: in deck.yml) and forbidden_file (the path of
<deck>.forbidden.txt, or null). The audience comes from deck.yml's
audience block (fall back to the audience: section of
.claude/rules/slide-profiles/<profile>.yml); state it in the report
header - it decides how much simplification is fair.
If sources is empty, write a one-paragraph report saying the deck
declares no sources so no claim on it can be verified, list the 5-10 most
load-bearing factual claims that would need one, and stop. Do not fact-check
against your own memory of the field; memory is not a source.
Step 1: read every source
Read each entry of sources end to end before reading the slides:
- A path (absolute, or relative to the repo root) is read with Read. For W02 and other lecture decks these are vault research notes; read them as the source of record even though they live outside this repo.
- A URL is fetched with WebFetch.
- A source that cannot be read is reported as such, by name, and the claims that depended on it are marked unverifiable - never silently skipped.
Read forbidden_file too, when it exists (one term per line, # comments).
Step 2: compare the slides against the sources
Walk every slide of the qmd and check, claim by claim:
Dates
- Every year, month, or "in 20XX" on a slide appears in a source with the
same value. Timeline slides (
.timelineitems) are checked entry by entry.
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 · 140 lines · 57 tokens per session scan A b5498acc1fc2
domain-reviewer is an agent published in the GitHub repository alohays/paper2pr (6 stars, last pushed 6d ago), licensed MIT. It adds 57 tokens to every session and 1,496 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.
Other agents, from other repositories
apa-specialist
APA 7th edition compliance specialist for academic manuscripts, covering citation formatting, table/figure styling, document structure, and Quarto/papaja implementation.
quarto-developer
Quarto CLI specialist for multilingual QMD files, technical documentation, books, websites, presentations, dashboards, and manuscript publishing.
jigsawr-developer
Specialized agent for jigsawR package development covering puzzle generation, pipeline integration, PILES notation, ggpuzzle layers, Quarto docs, and Shiny app.
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
AVM Owner Triage
Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.