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discussion-section-architect讨论部分建筑师

Agent Skill

discussion-section-architect 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

5,268

周安装

224

GitHub Stars

公开资料未说明

下载量

1,846
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:discussion-section-architect(讨论部分建筑师)
来源仓库:https://github.com/aipoch-ai/discussion-section-architect
安装命令:
openclaw skills install discussion-section-architect
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install discussion-section-architect

简介

构建学术论文或报告的讨论章节框架。

  • 解释研究发现、对比前人工作并提出未来方向。
  • 支持逻辑衔接、结论强化与局限说明。
  • 输入为研究结果摘要与背景文献。适用宿主包括 OpenClaw,接入前应确认版本、权限和运行环境要求。
  • 输出为完整段落与写作建议。discussion-section-architect 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

name
discussion-section-architect
description
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.
allowed-tools
Read Write Bash Edit
license
MIT
metadata
skill-author
AIPOCH
version
1.0

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

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

87.71%
按下载量换算1,619

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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