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Agent Skill · 研究检索

felo-twitter-writer(费洛推特作家)

felo-twitter-writer 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。

felo-twitter-writer 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为需要联网;许可证为 MIT-0,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 32,343。

总安装 2,540周安装 108GitHub Stars 公开资料未说明下载 890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-0
版本
1.0.0

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:felo-twitter-writer(费洛推特作家)
来源仓库:https://github.com/wangzhiming1999/felo-twitter-writer
安装命令:
openclaw skills install felo-twitter-writer
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 felo-twitter-writer

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。

felo-twitter-writer 是双模式 Twitter/X 写作工具,支持风格分析与内容生成。适合在 OpenClaw 中根据账号风格或主题快速生成推文内容。通过 openclaw skills install felo-twitter-writer 命令安装。

需确认权限范围及是否涉及外部 API 调用或敏感操作。适用宿主包括 OpenClaw,接入前应确认版本、权限和运行环境要求。

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 OpenClaw;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 openclaw skills install felo-twitter-writer;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

    它需要需要联网,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

felo-twitter-writer 怎么安装?

在终端执行 openclaw skills install felo-twitter-writer。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

felo-twitter-writer 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。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。

felo-twitter-writer 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

felo-twitter-writer 是免费的吗?

来源标注的许可证是 MIT-0。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。

felo-twitter-writer 用的人多吗?

公开数据是累计安装 2,540 次,近一周安装 108 次,下载 890 次。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。

felo-twitter-writer 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。

先想清楚的地方

  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 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 OpenClaw,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
felo-twitter-writer

费洛推特作家 · 本页

2,540—需要联网MIT-0有提醒

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

name
felo-twitter-writer
description
Dual-mode Twitter/X writing tool. Mode 1: input a Twitter account, auto-fetch popular tweets and extract a writing style DNA document. Mode 2: based on style DNA and a topic, compose high-quality tweets, threads, or X long-form posts. Use when users want to analyze Twitter style, extract writing style, write tweets, write threads, imitate someone's tweet style, or ghostwrite tweets.

Felo Twitter Writer Skill

Constraints (MUST READ FIRST)

These rules are mandatory. Violating any of them will produce incorrect behavior.

  1. This skill uses SuperAgent directly. All generation is handled by felo-superAgent/scripts/run_superagent.mjs with --skill-id twitter-writer. Do NOT attempt to generate tweet content yourself.
  1. ALWAYS use --json flag when calling SuperAgent. In Claude Code's Bash tool, stdout is always captured — it never streams directly to the user. JSON mode returns the full answer in a structured response. After the script finishes, read data.answer from the JSON output and print it verbatim as your response text.
  1. ALWAYS output data.answer verbatim. After the script finishes, print data.answer exactly as-is as your response text. Do NOT summarize, paraphrase, or add commentary around it.
  1. --live-doc-id is REQUIRED for every SuperAgent call. Follow these rules strictly:

- Reuse any live_doc_id already available in this session (from a prior SuperAgent or livedoc call) - If none: run node felo-livedoc/scripts/run_livedoc.mjs list --json, then find the first item where is_shared === false in data.items (list is sorted by modification time descending, so this gives the most recently modified private LiveDoc). Use its short_id. - If no is_shared === false item exists (or list is empty): run node felo-livedoc/scripts/run_livedoc.mjs create --name "Twitter Writer" --json, use data.short_id - NEVER use a LiveDoc where is_shared === true — shared LiveDocs belong to other projects and will cause a 502 error.

  1. Always persist state. After every SuperAgent call, extract thread_short_id and live_doc_short_id from the JSON response fields data.thread_short_id and data.live_doc_short_id. Use them in subsequent calls.
  1. Output language follows the user's input language. Default is en. Detect the user's language and pass the matching --accept-language value: ja for Japanese, en for English, ko for Korean, zh for Chinese. If unsure, use en.
  1. Do NOT pass --timeout to the SuperAgent script. The script manages its own connection lifecycle.
  1. Brand style selection for Mode 2 new conversations only. When starting a new conversation for content creation (Mode 2, no thread_short_id), you MUST attempt to fetch the TWITTER style library and offer the user a style choice BEFORE calling SuperAgent. The style is passed via --ext '{"brand_style_requirement":"..."}'. Full procedure in the Style Selection section below.

- Style category is always TWITTER (hardcoded — this skill only writes tweets). - --ext is only valid for new conversations. Never pass it in follow-up mode (--thread-id). - If the style library returns no entries, skip silently and proceed without --ext. - Mode 1 (style DNA extraction) does NOT use this step.

When to Use

Trigger this skill when the user wants to:

  • Analyze a Twitter/X account's writing style
  • Extract a writing style DNA document from tweets
  • Write, draft, or compose tweets / X posts
  • Write a Twitter thread (multi-tweet series)
  • Write an X long-form article / long post
  • Imitate or mimic someone's tweet style
  • Ghostwrite tweets on behalf of someone
  • Understand how a specific account writes

Trigger keywords:

  • English: analyze twitter style, twitter style analysis, extract writing style, style DNA, write a tweet, write tweets, draft a tweet, write a thread, twitter thread, X article, X long post, imitate tweet style, mimic tweet style, tweet in the style of, write like [account], X account analysis, analyze X account, ghostwrite tweets, how does [account] write
  • 日本語: ツイートを書く, ツイートスタイル分析, スタイルDNA, ツイートを模倣, Xアカウント分析, ツイートのスタイルを抽出, 〇〇風のツイートを書く, ツイートを代筆, Xアカウントを分析, このアカウントはどう書いている

Explicit commands: /felo-twitter-writer, use felo twitter writer

Do NOT use for:

  • General Twitter/X search only (use felo-x-search)
  • General SuperAgent conversation (use felo-superAgent)
  • Web search (use felo-search)

Two Modes

Mode 1 — Style DNA Extraction

When: User provides a Twitter/X account name and wants to understand or extract its writing style.

Steps:

Step 1: Fetch tweets via felo-x-search
node felo-x-search/scripts/run_x_search.mjs --id "USERNAME" --user --tweets --limit 30

Also fetch the account profile:

node felo-x-search/scripts/run_x_search.mjs --id "USERNAME" --user
Step 2: Obtain live_doc_id

Follow Constraint #4 above.

Step 3: Call SuperAgent with tweet content

Determine conversation mode first:

  • If no thread_short_id exists in this session → new conversation (pass --skill-id twitter-writer)
  • If thread_short_id already exists in this session → follow-up (pass --thread-id)

Replace LANG with the user's language: en (English), zh (Chinese), ja (Japanese), ko (Korean). See Constraint #6.

New conversation (first call in session):

node felo-superAgent/scripts/run_superagent.mjs \
  --query "/twitter-writer ENRICHED_QUERY_WITH_TWEET_CONTENT" \
  --live-doc-id "LIVE_DOC_ID" \
  --skill-id twitter-writer \
  --accept-language LANG \
  --json

Follow-up (thread_short_id already exists):

node felo-superAgent/scripts/run_superagent.mjs \
  --query "/twitter-writer ENRICHED_QUERY_WITH_TWEET_CONTENT" \
  --thread-id "THREAD_SHORT_ID" \
  --live-doc-id "LIVE_DOC_ID" \
  --accept-language LANG \
  --json

Query construction example:

Please analyze the following tweets from @USERNAME and extract a writing style DNA document. Cover dimensions such as: tone, sentence structure, opening hooks, closing calls-to-action, frequently used words, hashtag strategy, emoji usage, and any other distinctive patterns. Account bio: [BIO] Tweets: [TWEET_1] [TWEET_2] ...

Keep the query under 2000 characters. If tweet content is too long, include the most representative 10–15 tweets.

Step 4: Save state

Extract thread_short_id and live_doc_short_id from the JSON response fields data.thread_short_id and data.live_doc_short_id. Save for follow-up calls.


Mode 2 — Content Creation

When: User wants to create tweets, threads, or X long-form posts (with or without a style DNA).

Steps:

Step 1: Determine if style DNA is available
  • If Mode 1 was just run in this session → style DNA is already in the LiveDoc canvas, use follow-up mode
  • If user provides a style DNA directly → include it in the query
  • If user provides an account name → run Mode 1 first, then continue with Mode 2
  • If no style DNA → proceed to style library selection (Step 1.5)
Step 1.5: Brand Style Selection (new conversations only)

Only run this step when:

  • This is a new conversation (no thread_short_id in session), AND
  • Mode 1 was NOT just run (i.e., there is no existing thread carrying style DNA context)

Skip this step entirely when:

  • thread_short_id already exists (follow-up) — --ext has no effect in follow-up mode
  • Mode 1 was just run in this session — style context is already in the thread

1.5a. Check if user already specified a style:

If the user mentioned a style by name (e.g., "use my Bold Voice style") or pasted a style block, note it and skip to step 1.5d.

1.5b. Fetch the TWITTER style library (names only):

IMPORTANT: The style library output is very large (each Style DNA can be thousands of characters). Always use --json and extract only names/labels to avoid Bash tool output truncation. Never call run_style_library.mjs without --json for listing purposes.

node felo-superAgent/scripts/run_style_library.mjs --category TWITTER --accept-language LANG --json | node -e "
const d=require('fs').readFileSync('/dev/stdin','utf8');
const j=JSON.parse(d);
const list=j.list||[];
const user=list.filter(s=>!s.recommended);
const rec=list.filter(s=>s.recommended);
if(user.length) { console.log('[Your styles]'); user.forEach((s,i)=>{ const labels=(s.content?.labels?.LANG||s.content?.labels?.en||[]).join(', '); console.log((i+1)+'. '+s.name+(labels?' — '+labels:'')); }); }
if(rec.length) { console.log('[Recommended styles]'); rec.forEach((s,i)=>{ const labels=(s.content?.labels?.LANG||s.content?.labels?.en||[]).join(', '); console.log((user.length+i+1)+'. '+s.name+(labels?' — '+labels:'')); }); }
if(!list.length) console.log('(No styles found)');
"

Replace LANG with the user's language value (zh, ja, ko, en) in both --accept-language and inside the node script's labels?.LANG references.

Always pass --accept-language matching the user's language (same value used for SuperAgent).

1.5c. Handle the result:

If the list is empty: Skip silently. Proceed to Step 2 without --ext.

If styles are available: Output the COMPLETE list as plain text — every style returned by the API, grouped by type, numbered sequentially. NEVER use AskUserQuestion tool (it limits to 4 options and will silently drop styles). NEVER pre-select or filter styles on behalf of the user. Always append a "no preference" option as the last item. Then wait for the user's plain-text reply before proceeding.

Example presentation (adapt language to match user's language):

Here are the available Twitter writing styles — choosing one will make the output more accurate:

[Your styles]
1. My Bold Voice

[Recommended styles]
2. elonmusk — Shitposting provocateur
3. naval — Pithy aphorism master
...(list ALL styles, do not omit any)

0. No preference — use default style

1.5d. Build --ext from the chosen style:

After the user selects a style, fetch the full Style DNA for that specific style using --json and extract it in Node.js. Do NOT re-read the full text output — it will be truncated by the Bash tool.

node felo-superAgent/scripts/run_style_library.mjs --category TWITTER --accept-language LANG --json | node -e "
const d=require('fs').readFileSync('/dev/stdin','utf8');
const j=JSON.parse(d);
const s=(j.list||[]).find(s=>s.name==='CHOSEN_STYLE_NAME');
if(!s){process.stderr.write('Style not found\
');process.exit(1);}
const labels=(s.content?.labels?.LANG||s.content?.labels?.en||[]).join(', ');
const dna=s.content?.styleDna||'';
const block='Style name: '+s.name+'\
Style labels: '+labels+'\
Style DNA: '+dna;
console.log(JSON.stringify({brand_style_requirement:block}));
"

Replace CHOSEN_STYLE_NAME with the style name the user selected, and LANG with the language code.

Pass the output JSON directly as the --ext value:

--ext "$(node felo-superAgent/scripts/run_style_library.mjs --category TWITTER --accept-language LANG --json | node -e "
const d=require('fs').readFileSync('/dev/stdin','utf8');
const j=JSON.parse(d);
const s=(j.list||[]).find(s=>s.name==='CHOSEN_STYLE_NAME');
const labels=(s.content?.labels?.LANG||s.content?.labels?.en||[]).join(', ');
const dna=s.content?.styleDna||'';
const block='Style name: '+s.name+'\
Style labels: '+labels+'\
Style DNA: '+dna;
console.log(JSON.stringify({brand_style_requirement:block}));
")"

If the user chose "no preference" (option 0), do NOT pass --ext.

Step 2: Obtain live_doc_id

Follow Constraint #4. If Mode 1 was already run, reuse the same live_doc_id.

Step 3: Determine conversation mode
ConditionModeWhat to pass
No thread_short_id in this session (truly first call)New conversation--live-doc-id + --skill-id twitter-writer + --ext (if style chosen)
thread_short_id already exists in this session (all subsequent inputs, including after Mode 1)Follow-up--thread-id + --live-doc-id (NO --ext)
User says "new topic" / "start over" (clear thread_short_id)New conversation--live-doc-id + --skill-id twitter-writer + --ext (repeat Step 1.5)
Step 4: Call SuperAgent

Replace LANG with the user's language: en, zh, ja, ko. See Constraint #6.

New conversation without style (no thread_short_id, user chose no preference or list was empty):

node felo-superAgent/scripts/run_superagent.mjs \
  --query "/twitter-writer ENRICHED_QUERY" \
  --live-doc-id "LIVE_DOC_ID" \
  --skill-id twitter-writer \
  --accept-language LANG \
  --json

New conversation with brand style:

node felo-superAgent/scripts/run_superagent.mjs \
  --query "/twitter-writer ENRICHED_QUERY" \
  --live-doc-id "LIVE_DOC_ID" \
  --skill-id twitter-writer \
  --ext '{"brand_style_requirement":"Style name: darioamodei\
Style labels: Thoughtful long-form essays\
Style DNA: # Dario Amodei (@DarioAmodei) Tweet Writing Style DNA\
\
## Style Overview\
Dario writes like a serious intellectual...(full content, do NOT truncate)"}' \
  --accept-language LANG \
  --json

Follow-up (thread_short_id already exists in session):

node felo-superAgent/scripts/run_superagent.mjs \
  --query "/twitter-writer USER_FOLLOW_UP" \
  --thread-id "THREAD_SHORT_ID" \
  --live-doc-id "LIVE_DOC_ID" \
  --accept-language LANG \
  --json

Query construction guidelines:

  • Specify the content type: single tweet / thread / X long-form post
  • Specify the topic clearly
  • Include style DNA or reference account if available
  • Default to 3 versions unless the user specifies otherwise
  • Preserve the user's core intent; only add context and clarity

Query examples:

Please write 3 versions of a tweet about [TOPIC] in the style of @USERNAME (style DNA above). Each version should feel distinct — vary the tone, structure, or angle.
Based on the style DNA extracted above, write a Twitter thread (5–7 tweets) about [TOPIC]. Start with a strong hook tweet.
Write an X long-form post about [TOPIC] following the writing style we analyzed. Aim for ~500 words.
Step 5: Save state

Extract thread_short_id and live_doc_short_id from the JSON response fields data.thread_short_id and data.live_doc_short_id.


Mode Decision Logic

User input
  │
  ├── Contains account name + "analyze / style / DNA / how does X write"
  │   OR: アカウント名 + "分析 / スタイル / DNA / どう書いている"
  │     → Mode 1 (Style DNA Extraction) — skip style library step
  │
  ├── Contains account name + "write / create / imitate / in the style of"
  │   OR: アカウント名 + "書いて / 作って / 風に / 真似て"
  │     → Mode 1 first → then Mode 2 (follow-up, skip style library step)
  │
  ├── Contains topic + "write / draft / tweet / thread / X post"
  │   OR: トピック + "書いて / ツイート / スレッド / Xの投稿"
  │     → Mode 2 directly
  │         └── New conversation?
  │               YES → Step 1.5: fetch TWITTER styles, present to user, wait for choice
  │               NO  → follow-up, skip style library step
  │
  └── Ambiguous (e.g., "help me with tweets" / "ツイートを手伝って")
        → Ask user: do they want to analyze an account's style, or create content?

Complete Workflow Examples

Example A: Analyze an account's style

User: "Analyze @paulg's tweet style"

Step 1: Fetch tweets:

node felo-x-search/scripts/run_x_search.mjs --id "paulg" --user --tweets --limit 30
node felo-x-search/scripts/run_x_search.mjs --id "paulg" --user

Step 2: Get live_doc_id (list or create)

Step 3: Call SuperAgent (Mode 1 — no style library step):

node felo-superAgent/scripts/run_superagent.mjs \
  --query "/twitter-writer Please analyze the following tweets from @paulg and extract a writing style DNA document. Cover tone, sentence structure, opening hooks, closing CTAs, frequently used words, hashtag strategy, and emoji usage.\
\
Account bio: [BIO]\
\
Tweets:\
[TWEETS]" \
  --live-doc-id "LIVE_DOC_ID" \
  --skill-id twitter-writer \
  --accept-language en \
  --json

Step 4: Save thread_short_id and live_doc_short_id from JSON response fields data.thread_short_id and data.live_doc_short_id.


Example B: Create tweets with a reference style (Mode 1 → Mode 2)

User: "Write 3 tweets about startups in @paulg's style"

Step 1: Run Mode 1 to extract style DNA (same as Example A). Style library step is skipped because Mode 1 already establishes style context in the thread.

Step 2: Reuse live_doc_id from Mode 1.

Step 3: Follow-up call (continuing the same thread — thread_short_id from Mode 1, no --ext):

node felo-superAgent/scripts/run_superagent.mjs \
  --query "/twitter-writer Based on the @paulg style DNA extracted above, write 3 tweet variations about startups. Each should have a distinct tone and angle, within 280 characters." \
  --thread-id "THREAD_SHORT_ID" \
  --live-doc-id "LIVE_DOC_ID" \
  --accept-language en \
  --json

Example C: Write a thread directly (Mode 2, new conversation, with style selection)

User: "Write a Twitter thread about why most startups fail"

Step 1.5: New conversation, no existing thread → fetch TWITTER styles (names only):

node felo-superAgent/scripts/run_style_library.mjs --category TWITTER --accept-language en --json | node -e "
const d=require('fs').readFileSync('/dev/stdin','utf8');
const j=JSON.parse(d);
const list=j.list||[];
const user=list.filter(s=>!s.recommended);
const rec=list.filter(s=>s.recommended);
if(user.length){console.log('[Your styles]');user.forEach((s,i)=>{const labels=(s.content?.labels?.en||[]).join(', ');console.log((i+1)+'. '+s.name+(labels?' — '+labels:''));});}
if(rec.length){console.log('[Recommended styles]');rec.forEach((s,i)=>{const labels=(s.content?.labels?.en||[]).join(', ');console.log((user.length+i+1)+'. '+s.name+(labels?' — '+labels:''));});}
if(!list.length)console.log('(No styles found)');
"

Present to user:

Here are the available Twitter writing styles — choosing one will make the output more accurate:

[Your styles]
1. My Bold Voice

[Recommended styles]
2. darioamodei

0. No preference — use default style

User replies: 1

Step 2: Get live_doc_id.

Step 3: New conversation with chosen style — extract full Style DNA via --json and pass as --ext:

node felo-superAgent/scripts/run_superagent.mjs \
  --query "/twitter-writer Write a Twitter thread (6–8 tweets) about why most startups fail. Start with a strong hook tweet that grabs attention. Each tweet should stand alone but flow naturally into the next." \
  --live-doc-id "LIVE_DOC_ID" \
  --skill-id twitter-writer \
  --ext "$(node felo-superAgent/scripts/run_style_library.mjs --category TWITTER --accept-language en --json | node -e "
const d=require('fs').readFileSync('/dev/stdin','utf8');
const j=JSON.parse(d);
const s=(j.list||[]).find(s=>s.name==='My Bold Voice');
const labels=(s.content?.labels?.en||[]).join(', ');
const block='Style name: '+s.name+'\
Style labels: '+labels+'\
Style DNA: '+s.content.styleDna;
console.log(JSON.stringify({brand_style_requirement:block}));
")" \
  --accept-language en \
  --json

Step 4: Save thread_short_id and live_doc_short_id from JSON response fields data.thread_short_id and data.live_doc_short_id.


Example D: Iterate on generated content (follow-up, no style step)

User: "Make the 2nd tweet more humorous and add some emojis"

Already have thread_short_id and live_doc_id from the previous call. This is a follow-up — do NOT fetch styles again, do NOT pass --ext.

node felo-superAgent/scripts/run_superagent.mjs \
  --query "/twitter-writer Please revise the 2nd tweet generated above. Make the tone more humorous and lighthearted, and add appropriate emojis. Keep the original intent intact." \
  --thread-id "THREAD_SHORT_ID" \
  --live-doc-id "LIVE_DOC_ID" \
  --accept-language en \
  --json

Save updated thread_short_id and live_doc_short_id from JSON response fields data.thread_short_id and data.live_doc_short_id.


Example E: User specifies style by name

User: "Write a tweet about AI trends using my 'Bold Voice' style"

Step 1.5a: User already named the style → extract full Style DNA via --json. No need to ask the user again.

Step 3: New conversation with that style:

node felo-superAgent/scripts/run_superagent.mjs \
  --query "/twitter-writer Write a tweet about AI trends" \
  --live-doc-id "LIVE_DOC_ID" \
  --skill-id twitter-writer \
  --ext "$(node felo-superAgent/scripts/run_style_library.mjs --category TWITTER --accept-language en --json | node -e "
const d=require('fs').readFileSync('/dev/stdin','utf8');
const j=JSON.parse(d);
const s=(j.list||[]).find(s=>s.name==='My Bold Voice');
const labels=(s.content?.labels?.en||[]).join(', ');
const block='Style name: '+s.name+'\
Style labels: '+labels+'\
Style DNA: '+s.content.styleDna;
console.log(JSON.stringify({brand_style_requirement:block}));
")" \
  --accept-language en \
  --json

Example F: Style library is empty

User: "Write a tweet about the new product launch"

Step 1.5b: Fetch styles (names only):

node felo-superAgent/scripts/run_style_library.mjs --category TWITTER --accept-language en --json | node -e "
const d=require('fs').readFileSync('/dev/stdin','utf8');
const j=JSON.parse(d);
if(!(j.list||[]).length)console.log('(No styles found)');
else console.log((j.list||[]).map(s=>s.name).join('\
'));
"

Output: (No styles found)

Skip silently. Proceed directly without --ext:

node felo-superAgent/scripts/run_superagent.mjs \
  --query "/twitter-writer Write a tweet about the new product launch. Provide 3 versions with different tones." \
  --live-doc-id "LIVE_DOC_ID" \
  --skill-id twitter-writer \
  --accept-language en \
  --json

Example G: User chooses no preference

User: "Write a tweet about a new product launch"

Step 1.5: Fetch styles, present list. User replies: 0 (no preference).

Proceed without --ext:

node felo-superAgent/scripts/run_superagent.mjs \
  --query "/twitter-writer Write 3 tweets about a new product launch, each with a slightly different tone." \
  --live-doc-id "LIVE_DOC_ID" \
  --skill-id twitter-writer \
  --accept-language en \
  --json

Error Handling

ScenarioAction
Account not found or no tweets returnedInform user, suggest trying a different username or providing tweet samples manually
FELO_API_KEY not setStop and show setup instructions (same as felo-superAgent SKILL.md)
SuperAgent call failsCheck live_doc_id validity; retry once with the same parameters
Style library fetch failsLog warning to stderr, skip silently, proceed without --ext
User asks for Mode 2 with no style DNA and no accountProceed to Step 1.5 (style library selection)
User explicitly requests a new canvasCreate a new LiveDoc: node felo-livedoc/scripts/run_livedoc.mjs create --name "Twitter Writer" --json
Tweet content too long for query (>2000 chars)Trim to the 10–15 most representative tweets; prioritize high-engagement ones

References

平台分布

OpenClaw

98.5%
按下载量换算877

安全审计

VirusTotal

可疑

ClawScan

可疑

Static analysis

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

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