discussion-section-architect

Structures and writes discussion sections for academic papers and research reports. Use when writing a discussion section, interpreting research results, connecting findings to existing literature, addressing study limitations, synthesizing conclusions, or drafting any part of an academic discussion. Helps researchers organize arguments, contextualize data, and produce clear, publication-ready discussion prose.

Safety Notice

This listing is from the official public ClawHub registry. Review SKILL.md and referenced scripts before running.

Copy this and send it to your AI assistant to learn

Install skill "discussion-section-architect" with this command: npx skills add aipoch-ai/discussion-section-architect

Discussion Section Architect

Quick Start

  1. Provide your research question, key results, and any prior literature you want to reference.
  2. Choose a structure (see workflows below).
  3. Generate a draft discussion section with clearly organized subsections.
  4. Run the Draft → Revise loop (see below).

Core Capabilities

1. Interpret and Contextualize Results

  • State whether results support or contradict the original hypothesis.
  • Explain unexpected findings with reasoned interpretations.
  • Quantify effect sizes or patterns when relevant.

Example prompt input:

Results: Group A showed a 23% reduction in symptom severity (p=0.003) vs. control.
Hypothesis: Intervention would reduce symptom severity.
Task: Interpret this result for the discussion section.

Example output excerpt:

The 23% reduction in symptom severity (p=0.003) supports the primary hypothesis.
This effect size is clinically meaningful and consistent with the mechanistic
rationale proposed in the introduction...

2. Connect Findings to Existing Literature

  • Identify studies that corroborate the findings.
  • Highlight where results diverge from prior literature and offer explanations.
  • Use hedged academic language appropriate to the field.

Example:

Finding: Effect was stronger in older participants.
Literature: Smith et al. (2019) found age-moderated responses in a similar cohort.
Task: Connect finding to literature.

Output:

The age-moderated effect aligns with Smith et al. (2019), who reported attenuated
responses in younger adults. One possible explanation is differential receptor
sensitivity across age groups, as suggested by...

3. Address Limitations

Draft a limitations subsection that is honest but does not undermine the contribution:

Limitation: [Describe constraint]
Impact: [How it affects interpretation]
Mitigation / Future direction: [How it could be addressed]

4. Synthesize Conclusions

Generate a closing paragraph that:

  • Restates the core finding in plain language.
  • States the theoretical or practical contribution.
  • Ends with a forward-looking statement about implications or next steps.

Recommended Discussion Structure

1. Opening: Restate the research question and summarize the key finding (2–3 sentences).
2. Interpretation: Explain what the results mean mechanistically or theoretically.
3. Comparison to Literature: Agree/contrast with prior studies; explain divergences.
4. Implications: Theoretical contributions and/or practical applications.
5. Limitations: Honest scope boundaries with future directions.
6. Conclusion: Synthesis and forward-looking close.

Draft → Revise Loop

Use this iterative workflow after generating an initial draft:

Step 1 — Draft: Generate the full discussion section using the structure above.

Step 2 — Check: Review against the checklist:

  • Each finding from the Results section is explicitly addressed.
  • Claims are supported by citations or logical reasoning — not stated as facts.
  • Unexpected or null results are acknowledged and interpreted.
  • Limitations are stated without dismissing the study's contribution.
  • No new data or results are introduced in the discussion.
  • Hedged language used appropriately (e.g., "suggests," "indicates," "may reflect").
  • Conclusion ties back to the original research question.

Step 3 — Revise: For each failed checklist item, revise only the affected paragraph(s).

Step 4 — Re-check: Re-run the checklist on revised paragraphs to confirm resolution before finalizing.


References

  • references/guide.md - Detailed documentation
  • references/examples/ - Sample inputs and outputs

Skill ID: 950 | Version: 1.0 | License: MIT

Source Transparency

This detail page is rendered from real SKILL.md content. Trust labels are metadata-based hints, not a safety guarantee.

Related Skills

Related by shared tags or category signals.

Research

Batch Content Factory

Multi-platform content production line. Automates the entire workflow from topic research to content creation. Suitable for self-media operators producing hi...

Registry SourceRecently Updated
Research

Fund Analyzer Pro

[何时使用]当用户需要基金深度分析时;当用户说"分析这个基金""基金对比""基金诊断""基金经理分析"时;当检测到基金代码/基金名称/投顾策略时触发。整合天天基金 API+ 且慢 MCP,提供单一基金分析/基金比较/基金诊断/持仓诊断/基金经理/机会分析/投资方式/报告信号八大模块。新增信号监控提醒功能(sign...

Registry SourceRecently Updated
Research

FN Portrait Toolkit

Financial report footnote extraction and analysis tool for Chinese A-share listed companies. Use when: (1) User wants to extract financial note data from ann...

Registry SourceRecently Updated
Research

流式AI检索问答技能

通用流式AI检索问答技能 — 为任意行业应用提供四步流式分析交互界面。 触发场景:用户输入关键词 → AI自动执行:理解意图 → 检索知识库 → 流式生成 → 来源标记 → 完整回答。 当需要实现以下任意场景时激活: (1) AI搜索框 / 智能咨询组件重构 (2) 知识库问答(医疗/法律/金融/教育等垂直领域)...

Registry SourceRecently Updated