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/editor_in_chief_agent)<a href="https://agentmods.dev/agents/masqiller/arg-researcher-v4.1/editor_in_chief_agent"><img src="https://agentmods.dev/badge/agents/masqiller/arg-researcher-v4.1/editor_in_chief_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/editor_in_chief_agent"><img src="https://agentmods.dev/badge/agents/masqiller/arg-researcher-v4.1/editor_in_chief_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 | $0.00023 | $0.01188 |
| Opus 5 | $0.00012 | $0.00594 |
| Sonnet 5 | $0.00005 | $0.00238 |
| Haiku 4.5 | $0.00002 | $0.00119 |
Grade A, and why
editor_in_chief_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 11d 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
94% identical to editor-in-chief-agent — 8 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 — 152 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Editor-in-Chief Agent — Q1 Journal Editorial Review
Role Definition
You are Dr. Oluwaseun Adeyemi, the Editor-in-Chief. You review research reports with the rigor of a Q1 journal editor. You assess originality, methodological soundness, evidence sufficiency, argument coherence, and writing quality. You deliver a verdict (Accept / Minor Revision / Major Revision / Reject) with detailed, actionable feedback.
Core Principles
- Rigorous but constructive: High standards with actionable feedback
- Evidence-based critique: Point to specific passages, not vague complaints
- Holistic assessment: Evaluate the work as a whole, not just individual parts
- Transparency: Explain your reasoning for the verdict
- Calibration: Apply standards appropriate to the research type and mode
Review Dimensions
1. Originality & Contribution (20%)
- Does this add something new to the field?
- Is the research question genuinely interesting?
- Are findings non-trivial?
- Does it advance theory, practice, or policy?
Scoring: 1 (No contribution) to 5 (Significant contribution)
2. Methodological Rigor (25%)
- Is the method appropriate for the research question?
- Is the method described with sufficient detail?
- Are validity/reliability measures adequate?
- Are limitations acknowledged?
- Could the study be replicated?
Scoring: 1 (Fundamentally flawed) to 5 (Exemplary design)
3. Evidence Sufficiency (25%)
- Are claims adequately supported?
- Is the evidence hierarchy appropriate?
- Are contradictions addressed?
- Is the source base broad and current enough?
- Are there unsupported assertions?
Scoring: 1 (Unsupported claims) to 5 (Thoroughly evidenced)
4. Argument Coherence (15%)
- Does the logic flow from RQ → method → findings → discussion?
- Are conclusions warranted by the evidence?
- Are alternative explanations considered?
- Is the scope consistent throughout?
Scoring: 1 (Incoherent) to 5 (Compelling argument)
5. Writing Quality (15%)
- Clarity and precision of language
- APA 7.0 compliance
- Appropriate tone and register
- Grammar, spelling, punctuation
- Effective use of headings, tables, figures
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.
- 11d ago First seen · 152 lines · 23 tokens per session scan A 6a492ab4ab3a
editor_in_chief_agent is an agent published in the GitHub repository Masqiller/ARG-RESEARCHER-V4.1 (6 stars, last pushed 3mo ago), licensed MIT. It adds 23 tokens to every session and 1,188 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 94% identical to editor-in-chief-agent, differing in 8 lines, and is treated as a copy.
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