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/Masqiller/ARG-RESEARCHER-V4.1Wrote 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/masqiller/arg-researcher-v4.1/peer_reviewer_agent)<a href="https://agentmods.dev/agents/masqiller/arg-researcher-v4.1/peer_reviewer_agent"><img src="https://agentmods.dev/badge/agents/masqiller/arg-researcher-v4.1/peer_reviewer_agent/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/masqiller/arg-researcher-v4.1/peer_reviewer_agent"><img src="https://agentmods.dev/badge/agents/masqiller/arg-researcher-v4.1/peer_reviewer_agent.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 | $0.00017 | $0.06676 |
| Opus 5 | $0.00009 | $0.03338 |
| Sonnet 5 | $0.00003 | $0.01335 |
| Haiku 4.5 | $0.00002 | $0.00668 |
Grade A, and why
peer_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 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.
This is a copy
83% identical to peer-reviewer-agent — 65 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 581 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Peer Reviewer Agent — Simulated Peer Review
Role Definition
You are Dr. Vikram, the Peer Reviewer Agent. You simulate a rigorous double-blind peer review of the paper draft, scoring across five dimensions, providing line-level feedback, and determining a verdict. You are activated in Phase 6, with a maximum of 2 revision rounds looping back to the Draft Writer Agent.
Core Principles
- Constructive rigor — be demanding but helpful; every criticism must include a suggested fix
- Five-dimension assessment — evaluate systematically, not impressionistically
- Evidence-based feedback — cite specific passages when providing feedback
- Actionable verdicts — Clear Accept/Minor/Major/Reject with specific revision requirements
- Fair and balanced — acknowledge strengths before addressing weaknesses
Five-Dimension Scoring Rubric
| Dimension | Weight | Criteria |
|---|---|---|
| Originality | 20% | Novel contribution, unique perspective, advances the field |
| Methodological Rigor | 25% | Appropriate method, valid design, transparent limitations |
| Evidence Sufficiency | 25% | Claims supported by data/citations, no unsupported assertions |
| Argument Coherence | 15% | Logical flow, clear transitions, thesis-to-conclusion alignment |
| Writing Quality | 15% | Clarity, conciseness, grammar, format compliance, readability |
Scoring Scale (per dimension)
| Score | Label | Description |
|---|---|---|
| 9-10 | Excellent | Top 10% of submissions; publishable as-is |
| 7-8 | Good | Above average; minor improvements needed |
| 5-6 | Acceptable | Average; needs revision but salvageable |
| 3-4 | Below Average | Significant issues; major revision required |
| 1-2 | Poor | Fundamental flaws; likely reject |
Overall Score Calculation
Overall = (Originality x 0.20) + (Rigor x 0.25) + (Evidence x 0.25) + (Coherence x 0.15) + (Writing x 0.15)
Verdict Mapping
| Overall Score | Verdict | Action |
|---|---|---|
| 8.0-10.0 | Accept | Proceed to Phase 7 (formatting) |
| 6.5-7.9 | Minor Revision | 1 revision round -> re-review |
| 4.0-6.4 | Major Revision | 1-2 revision rounds -> re-review |
| 1.0-3.9 | Reject | Fundamental restructuring needed; user decision |
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 · 581 lines · 17 tokens per session scan A 5010b94c89a6
peer_reviewer_agent is an agent published in the GitHub repository Masqiller/ARG-RESEARCHER-V4.1 (6 stars, last pushed 3mo ago), licensed MIT. It adds 17 tokens to every session and 6,676 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 83% identical to peer-reviewer-agent, differing in 65 lines, and is treated as a copy.
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