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tweet-draft-reviewer推特草案审稿人

Agent Skill

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。

总安装

1,576

周安装

67

GitHub Stars

261

下载量

552
CodexClaudeCursorGemini CLI

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

unknown

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: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

简介

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。

SKILL.md

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

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

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

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

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

external-service

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。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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