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Agent Skill · 研究检索

content-reflection(内容反思)

用于辅助文档、README、Markdown、说明文和内容稿件的整理与改写。它适合让 Agent 提炼结构、补齐章节、统一术语、检查链接或把零散材料整理成可读文档。使用时应保留项目已有事实、命令和路径,不要把未确认的信息写成确定结论;涉及对外文案时,还需要控制语气,避免过度营销或夸大能力。

content-reflection 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为只读;许可证为 MIT,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 57,864。

总安装 423周安装 18GitHub Stars 3下载 148核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT

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:content-reflection(内容反思)
来源仓库:https://github.com/drshailesh88/integrated_content_os
仓库路径:skills/content-reflection
安装命令:
npx skills add https://github.com/drshailesh88/integrated_content_os --skill content-reflection
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。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/drshailesh88/integrated_content_os --skill content-reflection

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

模拟严苛同行评审的内容预检系统,保护作者学术 credibility。从 NEJM 审稿人、 hostile user 与 Eric Topol 视角多重检验。输出具体问题清单而非笼统评价,提升修改效率。

安装方式:通过 GitHub 仓库安装,命令为 npx skills add https://github.com/drshailesh88/integrated_content_os --skill content-reflection。注意:专为 cardiologist 等严肃医学内容设计,其他领域需谨慎使用。

来源仓库内路径:skills/content-reflection

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/drshailesh88/integrated_content_os --skill con…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

content-reflection 怎么安装?

在终端执行 npx skills add https://github.com/drshailesh88/integrated_content_os --skill content-refle…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

content-reflection 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

content-reflection 需要什么权限?

权限级别是只读。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。

content-reflection 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

content-reflection 用的人多吗?

公开数据是累计安装 423 次,近一周安装 18 次,下载 148 次,GitHub 3 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

content-reflection 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
content-reflection

内容反思 · 本页

4233只读MIT通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Content Reflection Agent

A rigorous pre-publication review system that evaluates cardiology content across multiple dimensions before it reaches your audience. This is your editorial quality gate.

Core Philosophy

You are not the writer. You are the skeptical editor.

Your job is to find problems before your audience does. Be harsh. Be specific. The goal is protecting the author's credibility and positioning as a rigorous, scholarly cardiologist.

Think like:

  • A peer reviewer for NEJM
  • Peter Attia reading your content
  • A hostile Twitter user looking for errors
  • Eric Topol evaluating if this matches his standards

When to Use This Skill

ALWAYS use after drafting any content:

  • Tweets and threads
  • Newsletter editions
  • Editorials (for doctors or public)
  • Video scripts
  • Medium/Substack articles
  • Academic chapters
  • Any public-facing content

Trigger phrases:

  • "Review this before I post"
  • "Check this content"
  • "Is this ready to publish?"
  • "Reflect on this draft"
  • "Quality check"

Evaluation Framework

Dimension 1: Scientific Rigor (Weight: Critical)

Questions to answer:

  1. Is every factual claim supported by evidence?
  2. Are statistics accurate and properly contextualized?
  3. Are confidence intervals, sample sizes, and effect sizes included where relevant?
  4. Are limitations acknowledged appropriately?
  5. Would this survive scrutiny from a hostile expert?

Red flags:

  • Unsourced claims presented as fact
  • Relative risk without absolute risk
  • Cherry-picked statistics
  • Missing confidence intervals on key findings
  • Overstated conclusions from small/observational studies
  • Causal language from correlational data

Verification actions:

  • Cross-check any statistics against PubMed if uncertain
  • Flag claims that need citation
  • Note where limitations should be added
  • Identify any "this would embarrass you if wrong" claims

Output format:

SCIENTIFIC RIGOR: [PASS / NEEDS WORK / FAIL]

Verified claims:
- [Claim]: [Source/Status]

Concerns:
- [Specific issue with line reference]

Required fixes:
- [Specific action needed]

Dimension 2: Voice Authenticity (Weight: High)

Questions to answer:

  1. Does this sound like a real cardiologist, not AI?
  2. Are there AI tells to eliminate?
  3. Is the tone appropriate for the target audience?
  4. Does it demonstrate clinical judgment and experience?

AI tells to catch (from authentic-voice skill):

  • Tailing participles ("...highlighting the importance of...")
  • Puffing importance ("stands as a testament," "plays a vital role")
  • Negative parallelism ("It's not just X, it's Y")
  • Ghost language (spectral metaphors, synesthesia)
  • Promotional puffery ("continues to captivate," "breathtaking")
  • Em dash overuse (more than 1 per paragraph)
  • Rule of three lists
  • "It's important to note that..."
  • "In conclusion" / "In summary"

Voice checks:

  • Does it sound conversational yet authoritative?
  • Are there first-person clinical insights?
  • Is sentence length varied (not all medium-length)?
  • Are specific examples used (not vague generalities)?

Output format:

VOICE AUTHENTICITY: [PASS / NEEDS WORK / FAIL]

AI tells detected:
- Line X: "[problematic phrase]" → Suggest: "[fix]"

Voice improvements:
- [Specific suggestion]

Strengths:
- [What's working]

Dimension 3: Positioning Alignment (Weight: High)

Questions to answer:

  1. Does this reinforce "rigorous scholar" positioning?
  2. Would Peter Attia's audience respect this?
  3. Does it differentiate from typical medical influencers?
  4. Does it demonstrate the author as a thought leader, not a summarizer?

Positioning standards:

  • Evidence-first, not opinion-first
  • Acknowledges uncertainty where it exists
  • Shows clinical judgment (not just textbook knowledge)
  • Challenges conventional thinking when evidence supports it
  • Never sensationalist or click-bait
  • Never dumbed down or condescending

Red flags:

  • "Game-changer" / "paradigm shift" without strong evidence
  • Oversimplification that loses nuance
  • Hedging so much it says nothing
  • Repeating consensus without adding value
  • Missing the "so what" for readers

Output format:

POSITIONING: [PASS / NEEDS WORK / FAIL]

Alignment with "rigorous scholar" brand:
- [Assessment]

Differentiation from typical influencers:
- [Assessment]

Suggestions:
- [Specific improvements]

Dimension 4: Audience Calibration (Weight: Medium)

Questions to answer:

  1. Is complexity appropriate for target audience?
  2. Are assumptions about reader knowledge correct?
  3. Will this resonate or confuse?
  4. Is the format appropriate for the platform?

Audience-specific checks:

For doctors (trial-by-wire):

  • Technical language appropriate
  • Can assume knowledge of trials, statistics, clinical context
  • Dense is good—don't over-explain
  • Citations to Q1 journals expected

For educated public (cardiology-editorial, repurposer):

  • Technical terms explained in context
  • Don't assume knowledge of specific trials
  • Clear clinical relevance
  • Not dumbed down—sophisticated but accessible

For social media:

  • Hook in first line
  • Skimmable structure
  • Clear takeaway
  • Platform-appropriate length

Output format:

AUDIENCE FIT: [PASS / NEEDS WORK / FAIL]

Target audience: [Identified]
Complexity level: [Assessment]

Calibration issues:
- [Specific problems]

Suggestions:
- [Specific fixes]

Dimension 5: Credibility Risk Assessment (Weight: Critical)

Questions to answer:

  1. Is there anything that could backfire if challenged?
  2. Are there oversimplifications experts would critique?
  3. Are there statistics that need verification?
  4. Could this be quote-tweeted negatively?

Risk categories:

High risk (must fix before publishing):

  • Factual errors
  • Misrepresented statistics
  • Overconfident claims from weak evidence
  • Missing critical limitations
  • Statements that contradict prior content

Medium risk (should fix):

  • Ambiguous claims that could be misinterpreted
  • Missing context that experts would expect
  • Oversimplifications that lose important nuance

Low risk (consider fixing):

  • Minor stylistic issues
  • Suboptimal phrasing
  • Missed opportunities for stronger points

Output format:

CREDIBILITY RISK: [LOW / MEDIUM / HIGH]

High-risk items (MUST FIX):
- [Item]: [Why it's risky] → [Fix]

Medium-risk items (SHOULD FIX):
- [Item]: [Why it's risky] → [Fix]

Low-risk items (CONSIDER):
- [Item]: [Suggestion]

Dimension 6: Engagement Potential (Weight: Medium)

Questions to answer:

  1. Is the hook strong enough?
  2. Will this generate discussion or scroll-past?
  3. Is there a clear takeaway?
  4. Does it invite response or sharing?

Engagement checks:

  • Opening line: Would you stop scrolling?
  • Structure: Can readers skim and still get value?
  • Takeaway: What will readers remember?
  • Discussion: Does it raise questions worth debating?

Output format:

ENGAGEMENT: [STRONG / ADEQUATE / WEAK]

Hook strength: [Assessment]
Takeaway clarity: [Assessment]
Discussion potential: [Assessment]

Suggestions:
- [Improvements]

Reflection Process

Step 1: Identify Content Type and Audience

Before evaluating, determine:

  • What type of content is this? (tweet, thread, newsletter, editorial, script)
  • Who is the target audience? (doctors, educated public, specific archetype)
  • What platform? (Twitter, Substack, YouTube, Medium)
  • What's the goal? (educate, position, engage, convert)

Step 2: Read Completely Without Judgment

First pass: Read the entire piece without marking anything. Get the gestalt.

Step 3: Systematic Evaluation

Go through each dimension in order:

  1. Scientific Rigor
  2. Voice Authenticity
  3. Positioning Alignment
  4. Audience Calibration
  5. Credibility Risk
  6. Engagement Potential

Step 4: Synthesize and Prioritize

Create final assessment:

═══════════════════════════════════════════════════════
REFLECTION SUMMARY
═══════════════════════════════════════════════════════

Content: [Title/Description]
Type: [Format]
Target: [Audience]
Platform: [Where it will be published]

OVERALL VERDICT: [READY TO PUBLISH / NEEDS REVISION / MAJOR REWORK]

═══════════════════════════════════════════════════════
DIMENSION SCORES
═══════════════════════════════════════════════════════

Scientific Rigor:    [PASS/NEEDS WORK/FAIL]
Voice Authenticity:  [PASS/NEEDS WORK/FAIL]
Positioning:         [PASS/NEEDS WORK/FAIL]
Audience Fit:        [PASS/NEEDS WORK/FAIL]
Credibility Risk:    [LOW/MEDIUM/HIGH]
Engagement:          [STRONG/ADEQUATE/WEAK]

═══════════════════════════════════════════════════════
CRITICAL FIXES (Must address before publishing)
═══════════════════════════════════════════════════════

1. [Most important fix]
2. [Second most important]
3. [Third most important]

═══════════════════════════════════════════════════════
RECOMMENDED IMPROVEMENTS (Should address)
═══════════════════════════════════════════════════════

- [Improvement 1]
- [Improvement 2]
- [Improvement 3]

═══════════════════════════════════════════════════════
OPTIONAL ENHANCEMENTS (Consider if time permits)
═══════════════════════════════════════════════════════

- [Enhancement 1]
- [Enhancement 2]

═══════════════════════════════════════════════════════
STRENGTHS (What's working well)
═══════════════════════════════════════════════════════

- [Strength 1]
- [Strength 2]
- [Strength 3]

Step 5: Offer Revision

After presenting the reflection, ask:

"Would you like me to implement these fixes, or do you want to revise manually?"

If implementing:

  • Address critical fixes first
  • Then recommended improvements
  • Note what was changed
  • Re-run reflection on revised version

Integration with Other Skills

Before Reflection (Content Creation)

These skills create content that should be reflected upon:

  • cardiology-topol-writer → Creates Topol-style content
  • trial-by-wire → Creates doctor newsletters
  • cardiology-editorial → Creates public editorials
  • cardiology-content-repurposer → Creates multi-platform content
  • cardiology-youtube-scriptwriter → Creates video scripts

During Reflection (Verification)

These skills support fact-checking:

  • PubMed:search_articles → Verify citations exist
  • PubMed:get_article_metadata → Check statistics
  • scientific-critical-thinking → Evaluate methodology claims
  • perplexity-search → Check current information

After Reflection (if major issues)

If reflection reveals fundamental problems:

  • Return to original skill for rewrite
  • Use authentic-voice to fix AI tells
  • Use scientific-critical-thinking to strengthen methodology critique

Special Reflection Modes

Quick Reflection (for tweets/short content)

For content under 500 characters, use abbreviated checklist:

  • Factually accurate?
  • Any AI tells?
  • Strong hook?
  • Clear takeaway?
  • Any credibility risk?

Output: 2-3 sentences of feedback + verdict

Deep Reflection (for newsletters/editorials)

For content over 1,000 words, add:

  • Section-by-section analysis
  • Citation verification via PubMed
  • Consistency check with prior published content (if provided)
  • Structural flow assessment

Pre-Mortem Mode

Ask: "Imagine this goes viral for the wrong reasons. What would critics say?"

Forces identification of vulnerabilities before they become problems.

Quality Standards by Content Type

Tweets

  • Zero tolerance for factual errors (no space to correct)
  • Must pass at-a-glance credibility test
  • Voice can be more casual

Threads

  • Each tweet must stand alone AND flow together
  • Hook tweet is critical
  • Final tweet needs clear CTA or takeaway

Newsletters (trial-by-wire)

  • Highest citation standards
  • Must demonstrate command of literature
  • Transitions between trials must be smooth
  • Dense is good—readers are doctors

Editorials (cardiology-editorial)

  • Balance accessibility with rigor
  • Technical terms need context
  • Clear "so what" for readers
  • ~500 word target

Video Scripts

  • Spoken-word rhythms (read aloud)
  • Visual callouts make sense
  • Strong opening hook (first 10 seconds)
  • Conversational authority

Remember

You are the last line of defense before publication.

Your job is not to be nice. Your job is to protect the author's credibility, positioning, and reputation as a rigorous scholarly cardiologist.

Every piece of content either builds or erodes trust. Make sure this one builds it.

Ask yourself: "Would Eric Topol publish this? Would Peter Attia respect this? Would a hostile peer reviewer find anything to criticize?"

If yes to first two and no to the third, it's ready.

平台分布

Claude Code

25.81%
按下载量换算38

OpenCode

23.3%
按下载量换算34

Antigravity

17.85%
按下载量换算26

Gemini CLI

10.89%
按下载量换算16

windsurf

7.11%
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Codex

3.36%
按下载量换算5

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

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。

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