Token导航 LogoToken导航

Agent Skill · 研究检索

tweet-draft-reviewer(推特草案审稿人)

tweet-draft-reviewer 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 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。

tweet-draft-reviewer 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,权限为调用外部服务;许可证信息还不明确,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 38,307。

总安装 1,576周安装 67GitHub Stars 261下载 552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
unknown

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:tweet-draft-reviewer(推特草案审稿人)
来源仓库:https://github.com/brianrwagner/ai-marketing-claude-code-skills
仓库路径:skills/tweet-draft-reviewer
安装命令:
npx skills add https://github.com/brianrwagner/ai-marketing-claude-code-skills --skill tweet-draft-reviewer
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 npx skills 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。

skills.shnpx skills
npx skills add https://github.com/brianrwagner/ai-marketing-claude-code-skills --skill tweet-draft-reviewer

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。

用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中根据关键词、任务场景或来源线索快速定位候选结果。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。

适用于需要快速获取特定领域信息的研发场景。支持主流 AI 编程工具集成使用。

来源仓库内路径:skills/tweet-draft-reviewer

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/brianrwagner/ai-marketing-claude-code-skills -…;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

    它需要调用外部服务,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

tweet-draft-reviewer 怎么安装?

在终端执行 npx skills add https://github.com/brianrwagner/ai-marketing-claude-code-skills --skill twe…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

tweet-draft-reviewer 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。

tweet-draft-reviewer 需要什么权限?

权限级别是调用外部服务。该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

tweet-draft-reviewer 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

tweet-draft-reviewer 用的人多吗?

公开数据是累计安装 1,576 次,近一周安装 67 次,下载 552 次,GitHub 261 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。

tweet-draft-reviewer 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。
  • 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

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 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。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 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
tweet-draft-reviewer

推特草案审稿人 · 本页

1,576261调用外部服务未明确通过

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

Tweet Draft Reviewer

Paste a tweet draft and get a score out of 10, a rule-by-rule breakdown, and a rewrite if the score is below 7. Takes 30 seconds. Saves you from posting something that sounds like a chatbot wrote it.

Built on 8 voice rules distilled from real content analysis — what separates high-engagement tweets from the ones that get skimmed.


How to Use

Single draft:

Review this tweet draft: [paste tweet here]

Batch scan:

Review all tweet drafts in my content/tweet-drafts/ folder.

Skill Instructions (for Claude Code)

When this skill is invoked, follow these phases exactly.


PHASE 1: INTAKE

Determine input mode:

Mode A — Direct paste: User provided draft text inline. Proceed to PHASE 2 with that text.

Mode B — Folder scan: User asked to review drafts folder. Run:

VAULT="${VAULT_PATH:-$(pwd)}"
find "$VAULT/content/tweet-drafts" -name "*.md" 2>/dev/null | while read f; do
  if ! grep -q 'reviewed: true' "$f" 2>/dev/null; then
    echo "UNREVIEWED:$f"
  fi
done

If no vault path was given and no content/tweet-drafts/ exists in the current directory, ask:

Where is your tweet drafts folder? (full path, e.g. /root/obsidian-vault/content/tweet-drafts)

Mode C — Ambiguous: No draft provided and no folder context. Ask:

Paste your tweet draft here, or tell me the path to your tweet-drafts folder and I'll scan it.

PHASE 2: ANALYZE

Apply all 8 rules to the draft. For each rule, record ✅ PASS or ❌ FAIL with a one-line reason.


The 8 Rules

Rule 1: No "I" opener

  • FAIL: First word is exactly I (standalone — not "In", "It", "If")
  • PASS: Anything else

Rule 2: Strong opener

  • FAIL: First sentence ends with ? OR starts with "Have you", "Do you", "Are you", "What if", "What would"
  • PASS: Declarative statement, specific number/fact, named scenario, or emotional setup

Rule 3: No AI tells

  • FAIL: Contains any of: delve, certainly, game-changing, game changer, it's worth noting, invaluable, unleash, revolutionize, transformative
  • PASS: None of those words detected

Rule 4: No generic closers

  • FAIL: Ends with (or contains near the end): what do you think, drop a comment, thoughts?, let me know in the comments, agree?, sound familiar?
  • PASS: Ends with a statement, directive, punchline, or thread hook

Rule 5: Corey Test (specificity)

  • FAIL: Uses vague language without specifics — "it changed how I work", "massive results", "so much better" — no numbers, names, or concrete outcomes
  • PASS: Contains at least one specific: a number, timeframe, named tool, or concrete result

Rule 6: Character count

  • PASS: 280 characters or fewer
  • THREAD PASS: Over 280 chars BUT sections are numbered (1/, 2/, 3/) or clearly separated with line breaks — count as PASS
  • FAIL: Over 280 chars with no thread formatting

Rule 7: Single point

  • FAIL: Makes 3+ distinct unrelated claims with no clear through-line
  • PASS: One core idea, even if supported by 2–3 details

Rule 8: Punchy rhythm

  • FAIL: Any sentence over 20 words OR preamble like "I've been thinking a lot about..." / "Something I've noticed recently is..."
  • PASS: Short sentences, no preamble, gets to the point by line 2 at latest

PHASE 3: OUTPUT

Print this exact format:

TWEET REVIEW
────────────

Score: X/10

Rule-by-Rule:
1. ✅/❌ No "I" opener — [reason]
2. ✅/❌ Strong opener — [reason]
3. ✅/❌ No AI tells — [reason]
4. ✅/❌ No generic closers — [reason]
5. ✅/❌ Corey Test — [reason]
6. ✅/❌ Character count — [reason + actual count]
7. ✅/❌ Single point — [reason]
8. ✅/❌ Punchy rhythm — [reason]

────────────

Scoring table (passes → score):

PassesScore
810/10
79/10
68/10
56/10
45/10
34/10
23/10
11/10
00/10

If score ≥ 7:

→ Ready to post. Use Typefully or your scheduler to queue it.

If score < 7 — add a rewrite:

Suggested Rewrite:

[rewritten tweet that fixes all failing rules]

PHASE 4: SELF-CRITIQUE

Before delivering the output, check:

  1. All 8 rules evaluated — Count the rule lines in your output. There must be exactly 8. If any are missing, add them.
  2. Score matches pass count — Count the ✅ marks. Verify the score matches the table above. Correct it if not.
  3. Rewrite quality — If a rewrite was provided, check it against all 8 rules mentally. Does it pass the ones the original failed? If the rewrite would score below 7 itself, rewrite it again.
  4. Reason quality — Each rule result must have a specific reason, not a generic one. "Too vague" is not enough — say what specifically is vague.

Fix anything that fails before delivering.


Example Review

Input:

I've been thinking a lot about how AI is really changing the way founders
approach content creation and productivity, and I think it's worth noting
that the teams who figure out async AI workflows are going to have a
massive advantage. What do you think about this?

Output:

TWEET REVIEW
────────────

Score: 2/10

Rule-by-Rule:
1. ❌ No "I" opener — Starts with "I've"
2. ❌ Strong opener — Slow setup, no hook, no specific fact
3. ❌ No AI tells — Contains "it's worth noting"
4. ❌ No generic closers — Ends with "What do you think about this?"
5. ❌ Corey Test — "massive advantage" is vague, no numbers or concrete outcome
6. ✅ Character count — 248 chars
7. ✅ Single point — Focused on async AI workflows
8. ❌ Punchy rhythm — Run-on sentence, preamble opener

────────────

Suggested Rewrite:

The founders winning right now aren't working harder.

They have agents running at 2am. Content drafted. Research done.
Queue processed.

By 7am they're reviewing output, not creating it.

Async AI ops is the new early morning routine.

Batch Mode Output

When scanning a folder, output one review block per file:

📄 content/tweet-drafts/linkedin-ai-post.md
[full review block]

📄 content/tweet-drafts/founder-ops.md
[full review block]

────────────
BATCH SUMMARY
Reviewed: 4 drafts
Ready to post (≥7): 2
Need rewrite (<7): 2

Requirements

  • Claude Code with bash tool access (for folder scan mode)
  • No external APIs — pure LLM reasoning for the review
  • Tweet drafts folder at content/tweet-drafts/ (optional — direct paste always works)
  • Files in the drafts folder are marked reviewed: true to skip them in future scans

平台分布

Codex

35.79%
按下载量换算198

Claude

26.33%
按下载量换算145

Cursor

18.91%
按下载量换算104

Gemini CLI

9.58%
按下载量换算53

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

调用外部服务

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

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。目前只有一个公开来源,建议同时核对源仓库。

继续浏览同类 Skills