Lord1Egypt Academic Paper Reviewer — 7-Agent Review System (Hermes Edition)
📄 License: CC BY-NC 4.0 · Copyright (c) 2026 Cheng-I Wu
🔗 Original: Imbad0202/academic-research-skills
🔄 Adaptation: Multi-agent review system implemented via delegate_task instead of Claude Code's internal agent system. All agent definitions, references, and quality standards preserved unchanged from original. This adaptation is distributed under the same CC BY-NC 4.0 license.
Quick Start
Review this paper for journal submission
Agent Team
| # | Agent | Role |
|---|---|---|
| 1 | intake_agent | Receive paper, determine review type |
| 2 | methodology_reviewer | Method rigor assessment |
| 3 | evidence_reviewer | Evidence sufficiency & citation quality |
| 4 | argument_reviewer | Logical coherence & argument structure |
| 5 | domain_reviewer | Domain expertise & literature positioning |
| 6 | editor_in_chief | Aggregate reviews → editorial decision |
| 7 | revision_coach | Convert reviews → actionable roadmap |
Hermes Execution
Full Mode: 5-Panel Parallel Review
delegate_task(tasks=[
{"goal": "Review manuscript methodology: design appropriateness, validity threats, replicability. Score 1-5.", "context": "Use agents/methodology_reviewer.md", "toolsets": ["file"]},
{"goal": "Review evidence: citation quality, source credibility, evidence hierarchy alignment. Score 1-5.", "context": "Use agents/evidence_reviewer.md", "toolsets": ["file"]},
{"goal": "Review argument: logical flow, claim-evidence alignment, counter-argument handling. Score 1-5.", "context": "Use agents/argument_reviewer.md", "toolsets": ["file"]},
{"goal": "Review domain positioning: literature coverage, theoretical grounding, contribution significance. Score 1-5.", "context": "Use agents/domain_reviewer.md", "toolsets": ["file"]}
])
Editorial Decision
delegate_task(goal="Aggregate all 4 reviewer reports. Apply weighted scoring (Method 30%, Evidence 25%, Argument 25%, Domain 20%). Issue editorial decision: Accept/Minor Revision/Major Revision/Reject with justification.", context="Use agents/editor_in_chief.md", toolsets=["file"])
Revision Roadmap
delegate_task(goal="Convert editorial decision + reviewer reports into structured Revision Roadmap: prioritized action items, estimated effort, dependency mapping.", context="Use agents/revision_coach.md", toolsets=["file"])
6 Modes
| Mode | Trigger | Agents |
|---|---|---|
full |
"Review paper" | All 7 |
re-review |
"Check revisions" | 2→3→4→6 |
quick |
"Quick review" | 6 only (EIC assessment) |
methodology-focus |
"Check methodology" | 2 only |
guided |
"Guide me to improve" | Socratic: 6 with user interaction |
calibration |
"Calibrate reviewer" | All + calibration metrics output |
Calibration Mode
Measures reviewer accuracy: FNR (False Negative Rate), FPR (False Positive Rate), AUC. Requires ground-truth labels on prior reviewed papers.
Critical Rules
- ⚠️ Reviewers are paper-blind (don't see author info)
- ⚠️ Every criticism must include specific actionable suggestion
- ⚠️ Calibration mode requires 5+ ground-truth papers
Security & Privacy
Multi-agent design disclosure: This skill delegates review tasks across multiple subagents via delegate_task. Manuscript content and intermediate review outputs are processed by these agents. Use only with manuscripts you are comfortable having processed through the AI provider's delegated-agent workflow. Remove confidential material not needed for review.
Tool access: Subagents are granted only file tools for reading/writing review outputs. No terminal, web, or system tools are exposed.
Agent files: The agents/ directory contains academic peer-review prompt templates (role definitions, scoring rubrics, methodology guidelines). These are task instructions loaded as context in delegate_task calls — NOT system prompt overrides.