Deep Research — Universal Academic Research (Hermes Edition)

📄 License: CC BY-NC 4.0 · Copyright (c) 2026 Cheng-I Wu
🔗 Original: Imbad0202/academic-research-skills v2.9.3
🔄 Adaptation: Multi-agent pipeline implemented via delegate_task instead of Claude Code's internal agent system. All agent definitions, references, templates, and quality standards preserved unchanged from original. This adaptation is distributed under the same CC BY-NC 4.0 license.

Model: Uses deepseek-v4-pro (1M context / 384K max_tokens) for all agent tasks.

Quick Start

Research the impact of AI on higher education quality assurance

Execution (Hermes orchestrator + delegate_task):

1. Scoping — delegate_task(research_question_agent + research_architect_agent)
2. Investigation — delegate_task(bibliography_agent + source_verification_agent)
3. Analysis — delegate_task(synthesis_agent + devils_advocate_agent)
4. Composition — delegate_task(report_compiler_agent)
5. Review — delegate_task(editor_in_chief + ethics_review + devils_advocate)
6. Revision — delegate_task(report_compiler_agent)

Hermes-Specific Execution Model

Core pattern: The main Hermes agent is the ORCHESTRATOR. Each research phase spawns subagents via delegate_task. The orchestrator manages:

• Phase sequencing and checkpoint gating
• Context handoff between phases
• Quality enforcement (failure = halt and get user input)
• Mode selection (full/quick/socratic/etc.)

Agent files at agents/ contain specialized prompts loaded as context in delegate_task.

Reference files at references/ provide domain knowledge injected as-needed.

Phase 1: SCOPING

Step 1.1: Research Question

delegate_task(
    goal="Transform the research topic '[USER_TOPIC]' into a precise, FINER-scored research question with scope boundaries. Output: RQ Brief with 2-3 sub-questions.",
    context="Use the agent definition at agents/research_question_agent.md for the full methodology. Apply FINER criteria (Feasible, Interesting, Novel, Ethical, Relevant).",
    toolsets=["file", "web"]
)

Step 1.2: Methodology Blueprint

delegate_task(
    goal="Design a methodology blueprint for the research question: [RQ_FROM_STEP_1]. Include: research paradigm, method selection, data strategy, analytical framework, validity criteria.",
    context="Use agent definition at agents/research_architect_agent.md. Reference: references/methodology_patterns.md.",
    toolsets=["file", "web"]
)

Checkpoint 1 — Devil's Advocate

delegate_task(
    goal="Review the Research Question Brief and Methodology Blueprint. Test for: RQ clarity, method appropriateness, scope validity. Output verdict: PASS or REVISE with specific feedback.",
    context="You are the Devil's Advocate. Use agent definition at agents/devils_advocate_agent.md. Reference: references/logical_fallacies.md, references/cross_agent_quality_definitions.md.",
    toolsets=["file"]
)

⚠️ CRITICAL issues → HALT. Require user correction. User must confirm before Phase 2.

Phase 2: INVESTIGATION

Step 2.1: Literature Search

delegate_task(
    goal="Conduct a systematic literature search for [RQ]. Output: search strategy, inclusion/exclusion criteria, PRISMA-style flow, annotated bibliography in APA 7.0.",
    context="Use agent definition at agents/bibliography_agent.md. Reference: references/apa7_style_guide.md, references/source_quality_hierarchy.md.",
    toolsets=["file", "web"]
)

Step 2.2: Source Verification

delegate_task(
    goal="Verify and grade all sources from the bibliography. Apply evidence hierarchy grading (Level I-VII), predatory journal screening, conflict-of-interest flagging. Output: Verified & Graded Sources + Source Quality Matrix.",
    context="Use agent definition at agents/source_verification_agent.md. Reference: references/source_quality_hierarchy.md, references/cross_agent_quality_definitions.md.",
    toolsets=["file", "web"]
)

Phase 3: ANALYSIS

Step 3.1: Cross-Source Synthesis

delegate_task(
    goal="Synthesize findings across all verified sources. Identify themes, contradictions, knowledge gaps. Output: Synthesis Narrative + Gap Analysis with evidence convergence/divergence mapping.",
    context="Use agent definition at agents/synthesis_agent.md. Reference: references/argumentation_reasoning_framework.md, references/interdisciplinary_bridges.md.",
    toolsets=["file"]
)

Checkpoint 2 — Devil's Advocate

delegate_task(
    goal="Review the synthesis. Check for cherry-picking, confirmation bias, logic chain validity, alternative explanations. Output verdict: PASS or REVISE.",
    context="Use agent definition at agents/devils_advocate_agent.md. Reference: references/logical_fallacies.md.",
    toolsets=["file"]
)

Phase 4: COMPOSITION

delegate_task(
    goal="Compile a full APA 7.0 research report from all prior materials. Structure: Title → Abstract → Intro → Lit Review → Methodology → Findings → Discussion → Conclusion → References. Word count: 3,000-8,000.",
    context="Use agent definition at agents/report_compiler_agent.md. Reference: references/apa7_style_guide.md. Include all prior phase outputs as context.",
    toolsets=["file"]
)

Phase 5: REVIEW (3 agents in parallel)

# Run all three simultaneously
delegate_task(tasks=[
    {
        "goal": "Editorial review: assess originality, rigor, evidence sufficiency, argument coherence, writing quality. Verdict: ACCEPT/MINOR/MAJOR/REJECT with line feedback.",
        "context": "Use agent definition at agents/editor_in_chief_agent.md. Reference: references/apa7_style_guide.md.",
        "toolsets": ["file"]
    },
    {
        "goal": "Ethics review: AI disclosure compliance, attribution integrity, dual-use screening, fair representation. Verdict: CLEARED/CONDITIONAL/BLOCKED.",
        "context": "Use agent definition at agents/ethics_review_agent.md. Reference: references/ethics_checklist.md, references/irb_decision_tree.md.",
        "toolsets": ["file"]
    },
    {
        "goal": "Final vulnerability scan: strongest counter-argument test, significance check, alternative explanations. Verdict: PASS/REVISE.",
        "context": "Use agent definition at agents/devils_advocate_agent.md. Reference: references/logical_fallacies.md.",
        "toolsets": ["file"]
    }
])

Phase 6: REVISION

delegate_task(
    goal="Revise the full report addressing all Phase 5 feedback. Incorporate editorial, ethics, and devil's advocate insights. Max 2 revision loops. Remaining issues → Acknowledged Limitations section.",
    context="Use agent definition at agents/report_compiler_agent.md. Include all Phase 5 review outputs and the current draft.",
    toolsets=["file"]
)

Mode Selection

Before starting, determine the mode based on user intent:

Mode Selection Logic:

• User has clear RQ and needs full report → full
• User has vague idea, needs guidance → socratic
• User has paper to evaluate → review
• User needs quick summary → quick
• User only needs literature → lit-review
• User needs to verify claims → fact-check
• PRISMA-compliant review needed → systematic-review

When ambiguous between socratic and full, prefer socratic.

Socratic Mode

5-layer dialogue guiding users from vague ideas to concrete research questions.

Core principle: ⚠️ Never give direct answers. Guide through questions.

Agent (single delegate_task per layer):

delegate_task(
    goal="Layer [N] Socratic dialogue for research topic: [USER_TOPIC]. Previous layers: [LAYER_OUTPUTS]. Ask questions that probe [LAYER_FOCUS]. Never give answers.",
    context="Use agent definition at agents/socratic_mentor_agent.md. Reference: references/socratic_mode_protocol.md, references/socratic_questioning_framework.md.",
    toolsets=["file"]
)

Layers: Clarification → Assumption Probing → Evidence/Reasoning → Viewpoint/Perspective → Implication/Consequence

Auto-end after 10 rounds without convergence → suggest switching to full mode.

Systematic Review Mode

PRISMA 2020-compliant. Adds two extra agents:

# After Phase 2 bibliography:
delegate_task(goal="Assess risk of bias using RoB 2 (RCTs) and ROBINS-I (non-randomized). Traffic-light visualization.",
    context="Use agent definition at agents/risk_of_bias_agent.md. Reference: references/systematic_review_toolkit.md.",
    toolsets=["file"])

# After Phase 3 synthesis:
delegate_task(goal="Design and execute meta-analysis or narrative synthesis. Effect sizes, heterogeneity (I²), GRADE assessment.",
    context="Use agent definition at agents/meta_analysis_agent.md. Reference: references/systematic_review_toolkit.md.",
    toolsets=["file"])

Critical Rules (IRON RULES)

1. ⚠️ Every claim must have a citation — no unsupported assertions
2. ⚠️ Gray zone = FAIL — if you cannot confirm a reference exists, it does not go in the report
3. ⚠️ Devil's Advocate CRITICAL → HALT — explain the issue, require user correction
4. ⚠️ Ethics BLOCKED → HALT — list issues and remediation path
5. ⚠️ Max 2 revision loops — remaining issues become Acknowledged Limitations
6. ⚠️ User confirmation after Phase 1 — do not auto-continue
7. Vibe citing = forbidden — every reference must be independently verifiable
8. No phase skipping — complete each phase fully before moving to next

Orchestrator Checklist

Before starting each phase, the orchestrator (main Hermes agent) MUST:

1. Verify the previous phase checkpoint passed
2. Load the relevant agent file via read_file
3. Pass all prior outputs as context to delegate_task
4. Review subagent output before proceeding
5. Respect HALT conditions (ask user, don't auto-fix)

Failure Paths

Agent File References

All agent files are the original v2.9.3 definitions with unchanged methodology. They are loaded as context in delegate_task calls.

Output Language

Follow user's language. Academic terminology kept in English.

Anti-Patterns

Handoff to academic-paper

After research complete, these materials can be handed off:

1. Research Question Brief
2. Methodology Blueprint
3. Annotated Bibliography
4. Synthesis Report
5. [If socratic] INSIGHT Collection and Research Plan Summary

User says "now help me write a paper" → switch to academic-paper skill.

Security & Privacy

Multi-agent design disclosure: This skill delegates research tasks across multiple subagents via delegate_task. Research content and intermediate outputs are processed by these agents. Use only with research topics you are comfortable processing through the AI provider's delegated-agent workflow.

Tool access: Subagents are granted file tools (for writing output) and web tools (for literature search only). No terminal or system tools are exposed during review/composition phases.

Agent files: The agents/ directory contains academic research prompt templates (role definitions, methodology guidelines, quality rubrics). These are task instructions loaded as context in delegate_task calls — NOT system prompt overrides. Frontmatter in agent files (e.g., name:, description:) is metadata only.