# Handoff Example: deep-research → academic-paper This example demonstrates how deep-research full mode, after completing research, hands off to academic-paper to begin paper writing. --- ## Scenario Setup The user has completed deep-research full mode on the topic "AI-Assisted Quality Assurance in Higher Education: A Comparative Analysis of Implementation Strategies in East Asian Universities." Below is a summary of the research outputs. --- ## deep-research Output Summary ### 1. Research Question Brief (from research_question_agent) ```markdown ### Primary Research Question How do East Asian universities (Taiwan, Japan, South Korea) differ in their implementation strategies for AI-assisted quality assurance, and what factors explain the variation in adoption patterns? ### FINER Assessment | Criterion | Score | Justification | |-------------|-------|---------------| | Feasible | 4/5 | Public data + policy documents available | | Interesting | 5/5 | Timely: AI policy divergence across similar systems | | Novel | 4/5 | Few cross-national comparisons in this space | | Ethical | 5/5 | No human subjects; public policy analysis | | Relevant | 5/5 | Directly informs HEEACT and peer agencies | | **Average** | **4.6/5** | | ### Sub-questions 1. What AI-QA tools and frameworks have been adopted by accreditation agencies in Taiwan, Japan, and South Korea? 2. What institutional and policy factors facilitate or hinder AI-QA adoption? 3. To what extent do implementation outcomes align with stated policy objectives? ``` ### 2. Methodology Blueprint (from research_architect_agent) ```markdown - Paradigm: Pragmatist (comparative policy analysis) - Method: Qualitative comparative analysis (QCA) + document analysis - Data sources: - Policy documents (3 countries' QA frameworks) - Accreditation agency reports (HEEACT, JUAA/NIAD-QE, KCUE) - Published case studies and conference proceedings - Analytical framework: Diffusion of Innovation (Rogers) + Institutional Isomorphism (DiMaggio & Powell) - Validity: Triangulation across document types + member checking with QA practitioners ``` ### 3. Annotated Bibliography (from bibliography_agent) ```markdown 23 sources identified, 18 retained after quality screening: - 6 peer-reviewed articles (Level II-III evidence) - 4 accreditation agency reports (Level IV) - 3 policy documents (Level IV) - 3 conference proceedings (Level V) - 2 institutional case studies (Level V) Key themes identified: - AI adoption maturity gap (Taiwan > Korea > Japan in QA applications) - Regulatory divergence (Japan's cautious approach vs Korea's top-down push) - Data infrastructure as prerequisite (not just technology) ``` ### 4. Synthesis Report (from synthesis_agent) ```markdown ## Core Findings 1. **Adoption patterns cluster into 3 models**: - Taiwan: bottom-up experimentation (agency-led pilots) - South Korea: top-down mandate (ministry-driven framework) - Japan: cautious incrementalism (voluntary guidelines) 2. **Critical success factors** (converging evidence across all 3 countries): - Data infrastructure maturity - Accreditation agency technical capacity - University willingness to share data - Clear governance framework for AI decisions 3. **Key tension**: efficiency gains vs transparency concerns - All 3 countries report resistance from faculty regarding "black box" decisions - Only Korea has attempted regulatory response (AI Ethics in Education Act 2025) 4. **Evidence gap**: - No rigorous outcome studies yet (all countries < 3 years into implementation) - Student/faculty experience data almost entirely absent ## Contradictions Identified - Taiwan HEEACT reports "high adoption" but academic literature suggests most universities are still in pilot phase → definition of "adoption" varies ## Knowledge Gaps - Impact on accreditation outcomes (pass/fail rates) - Cost-effectiveness analysis - Faculty perceptions and behavioral changes ``` --- ## Handoff Instruction After completing deep-research, the user inputs: ``` Now help me write a paper based on this research ``` --- ## academic-paper intake_agent Auto-Detection **intake_agent Detection Process**: ``` Scanning available materials... [DETECTED] Research Question Brief - Source: deep-research / research_question_agent - Status: Complete (FINER 4.6/5) - Action: SKIP academic-paper Phase 1 (topic scoping) [DETECTED] Methodology Blueprint - Source: deep-research / research_architect_agent - Status: Complete (pragmatist QCA + document analysis) - Action: SKIP academic-paper Phase 2 (methodology design) - Note: Will integrate into Method section directly [DETECTED] Annotated Bibliography (18 sources, APA 7.0) - Source: deep-research / bibliography_agent - Status: Complete, quality-screened - Action: SKIP academic-paper literature search - Note: Will use as foundation for Literature Review section [DETECTED] Synthesis Report - Source: deep-research / synthesis_agent - Status: Complete (3 core findings + 1 contradiction + 2 gaps) - Action: SKIP academic-paper analysis phase - Note: Will structure Findings and Discussion sections around synthesis Materials Assessment: COMPREHENSIVE Recommended academic-paper mode: full (with accelerated pipeline) Estimated sections already covered: 60-70% Remaining work: Writing, formatting, argumentation, and polish ``` --- ## Skipped Steps and Reasons | academic-paper Step | Normal Workflow | After Handoff | Reason | |---------------------|---------|-----------|------| | Phase 1: Topic Scoping | intake_agent clarifies from scratch | SKIPPED | RQ Brief is complete | | Phase 2: Structure Planning | outline_agent designs structure | PARTIAL | Has Blueprint but needs conversion to paper structure | | Phase 3: Literature Search | literature_agent searches | SKIPPED | Bibliography is complete | | Phase 4: Literature Review Writing | review_writer_agent writes | ACTIVE | Has Synthesis but needs conversion to paper tone | | Phase 5: Methodology Writing | method_writer_agent writes | ACTIVE | Has Blueprint but needs expansion to full paragraphs | | Phase 6: Findings Writing | findings_writer_agent writes | ACTIVE | Has Synthesis but needs expanded argumentation | | Phase 7: Discussion Writing | discussion_writer_agent writes | ACTIVE | Needs original discourse (not direct copy of Synthesis) | | Phase 8: Intro + Conclusion | bookend_agent writes | ACTIVE | Needs to be written based on full text | | Phase 9: Abstract + Formatting | format_agent processes | ACTIVE | Needs full text completion first | | Phase 10: Self-Review | review_agent reviews | ACTIVE | Must be executed | --- ## Post-Handoff academic-paper Actual Workflow ``` === academic-paper: Accelerated Pipeline === Step 1: STRUCTURAL MAPPING [outline_agent] - Input: RQ Brief + Methodology Blueprint + Synthesis Report - Output: Complete paper outline, each section tagged with corresponding deep-research materials - Output example: I. Introduction - Context: AI in HE QA (from Synthesis background) - Problem: Cross-national variation unexplained - Purpose: Compare 3 East Asian models - RQ: [Directly cite RQ Brief] II. Literature Review - 2.1 AI in Quality Assurance (from Bibliography themes) - 2.2 Diffusion of Innovation framework (from Blueprint) - 2.3 Institutional Isomorphism (from Blueprint) - 2.4 East Asian HE systems comparison III. Methodology - 3.1 Research design: QCA + document analysis (from Blueprint) - 3.2 Case selection and data sources - 3.3 Analytical framework - 3.4 Validity and limitations IV. Findings - 4.1 Three adoption models (from Synthesis Finding 1) - 4.2 Critical success factors (from Synthesis Finding 2) - 4.3 Efficiency vs transparency tension (from Synthesis Finding 3) V. Discussion - 5.1 Theoretical implications - 5.2 Policy implications for accreditation agencies - 5.3 Practical recommendations - 5.4 Limitations (from Synthesis gaps + Blueprint validity) VI. Conclusion - Summary + Future research directions Step 2: SECTION WRITING (Parallel) [review_writer_agent] → Literature Review - Based on Annotated Bibliography and Synthesis, transform into a fluent literature review - Not sequential summaries, but thematic integration [method_writer_agent] → Methodology - Expand the Blueprint into complete methodology paragraphs - Add technical details and procedural explanation for QCA [findings_writer_agent] → Findings - Expand the Synthesis's 3 core findings into evidence-supported arguments - Each finding accompanied by specific cases and data - Address contradictions flagged in the Synthesis Step 3: DISCUSSION + BOOKENDS [discussion_writer_agent] → Discussion - Original discourse: dialogue between findings and theory - Does not repeat Findings; instead explains "why" - Integrates deep-research Knowledge Gaps as Future Research [bookend_agent] → Introduction + Conclusion - Introduction: from macro context to specific RQ - Conclusion: no new information, echoes RQ and looks to the future Step 4: ABSTRACT + FORMAT [format_agent] - Abstract: 150-250 words, IMRAD structure - APA 7.0 full-text formatting - Reference list cleanup (based on Bibliography + newly added citations) Step 5: SELF-REVIEW [review_agent] - Internal consistency check (RQ → Method → Findings → Discussion logic chain) - Citation completeness (every claim has a citation) - Format compliance - Verdict: Ready for submission / Needs revision ``` --- ## User-Facing Handoff Experience **academic-paper's Opening Message**: > I've read your complete outputs from the deep-research stage, including: > - Research Question Brief (FINER 4.6/5) > - Methodology Blueprint (QCA + document analysis) > - Annotated Bibliography (18 quality-screened sources) > - Synthesis Report (3 core findings + 2 knowledge gaps) > > Based on these materials, I've completed a preliminary plan for the paper outline. Here is the planned paper structure: > [Display outline] > > I have two questions that need your confirmation: > 1. What is your target journal? (This affects word limits and formatting requirements) > 2. Should the paper language be English or bilingual? > > Once confirmed, I'll begin writing. Because the research foundation is already comprehensive, I can skip the early exploration stages and proceed directly to paper writing. --- ## Notes 1. **Not copy-paste**: academic-paper does not directly copy deep-research outputs, but transforms them into the tone and format of an academic paper 2. **May discover new issues**: During the writing process, academic-paper agents may discover points missed by deep-research and will proactively supplement them 3. **Still requires user confirmation**: Target journal, language preference, specific formatting requirements still require user input 4. **Review recommendation auto-connects**: After paper completion, the user can continue with `academic-paper-reviewer` for formal review