| 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.
-
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.
-
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.
-
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.
-
--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.
-
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.
-
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.
-
Do NOT pass --timeout to the SuperAgent script. The script manages its own connection lifecycle.
-
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\n');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+'\nStyle labels: '+labels+'\nStyle 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+'\nStyle labels: '+labels+'\nStyle 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
| Condition | Mode | What 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\nStyle labels: Thoughtful long-form essays\nStyle DNA: # Dario Amodei (@DarioAmodei) Tweet Writing Style DNA\n\n## Style Overview\nDario 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.\n\nAccount bio: [BIO]\n\nTweets:\n[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+'\nStyle labels: '+labels+'\nStyle 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+'\nStyle labels: '+labels+'\nStyle 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('\n'));
"
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
| Scenario | Action |
|---|
| Account not found or no tweets returned | Inform user, suggest trying a different username or providing tweet samples manually |
FELO_API_KEY not set | Stop and show setup instructions (same as felo-superAgent SKILL.md) |
| SuperAgent call fails | Check live_doc_id validity; retry once with the same parameters |
| Style library fetch fails | Log warning to stderr, skip silently, proceed without --ext |
| User asks for Mode 2 with no style DNA and no account | Proceed to Step 1.5 (style library selection) |
| User explicitly requests a new canvas | Create 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
