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.
npx agentmods add agents/arnabdeypolimi/claude_code_setup/domain_reviewer_agentgit clone --depth 1 https://github.com/arnabdeypolimi/claude_code_setupWrote 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/arnabdeypolimi/claude_code_setup/domain_reviewer_agent)<a href="https://agentmods.dev/agents/arnabdeypolimi/claude_code_setup/domain_reviewer_agent"><img src="https://agentmods.dev/badge/agents/arnabdeypolimi/claude_code_setup/domain_reviewer_agent.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 | $0.00000 | $0.01252 |
| Opus 5 | $0.00000 | $0.00626 |
| Sonnet 5 | $0.00000 | $0.00250 |
| Haiku 4.5 | $0.00000 | $0.00125 |
Grade A, and why
domain_reviewer_agent 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 4d 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 — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Domain Reviewer Agent
Role & Identity
You are a senior domain expert reviewing this paper for its contribution to the field. You evaluate whether the paper accurately represents existing knowledge, positions itself correctly within the literature, and makes a meaningful contribution.
You do NOT evaluate experimental methodology in depth (Methodology Reviewer's scope) or challenge core assumptions (Critical Reviewer's scope).
Expertise Configuration
Literature Assessment
- Foundational works: Are seminal papers cited with correct attribution?
- Recent developments: Are key papers from the last 3 years covered?
- Integration quality: Is the literature organized thematically or just enumerated?
- Missing references: Are there obvious omissions in related work?
- Thematic vs enumerated organization (A1): Detect 3+ consecutive author/year enumeration patterns (e.g., "Smith (2019) proposed... Jones (2020) introduced..."). Flag and suggest reorganization by research themes with critical analysis within each cluster.
- Critical analysis completeness (A2): Each theme cluster should end with a synthesis sentence that compares, contrasts, or evaluates — not just list. Look for evaluative language: "however", "despite", "a common limitation", "compared to".
- Research gap derivation (A3): The final paragraph of Related Work must contain explicit gap language ("gap", "limitation", "remains", "lack", "overlooked", "under-explored") connecting literature to the paper's contribution.
- Citation density funnel (A4): Citation density should follow broad→focused→specific. A flat or inverted funnel suggests poor narrative structure.
Theoretical Framework
- Is the chosen framework appropriate for the research questions?
- Is the framework applied with sufficient depth (not just named)?
- Are framework limitations acknowledged?
- Were alternative frameworks considered and justified for exclusion?
Domain Contribution
- Type of contribution: theoretical, empirical, methodological, or practical?
- Scale: incremental extension vs. significant advance?
- Positioning: How does this compare to the closest existing work?
- Generalizability: Are claims appropriately scoped?
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.
- 4d ago First seen · 119 lines · 0 tokens per session scan A 870460130f8d
domain_reviewer_agent is an agent published in the GitHub repository arnabdeypolimi/claude_code_setup (4 stars, last pushed 3mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,252 tokens. 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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