legioncodeinc Facebook Voice Creator
Build a user's personal voice skill from their real Facebook writing. The output is a
skill like mario-aldayuz-voice: a lean SKILL.md plus fingerprint, anti-AI rules,
verbatim corpus, and approved samples - all derived from what the user actually wrote,
never from guesses.
Why Facebook data: a data export contains months of the user's unfiltered writing across every register they have - long rants, quick jokes, DMs, comments. That beats any interview or questionnaire. The whole method is: real words first, analysis second, imitation last.
Process overview
Run these phases in order. Use the AskUserQuestion tool at every decision point - the reference guides specify each question and its recommended answer.
Phase 1 - Export (user-driven, ~5 minutes of clicking)
Read references/facebook-export-guide.md and walk the user through the Facebook
export flow step by step, showing them the screenshots in assets/ as you go.
Critical settings to confirm with AskUserQuestion (recommended answers first):
- Customize information: Posts (required), Messages (optional), Profile information (optional). Nothing else.
- Date range: 6 months or 1 year.
- Format: JSON (not the HTML default - this matters).
- Media quality: Lower.
Phase 2 - Wait (async, 2-3 hours)
Facebook builds the export in roughly 2-3 hours and the user has only 4 days to download it. Do not block - tell the user to return with the zip. If there is other work in this conversation, proceed with it.
Phase 3 - Process the upload
When the user uploads the .zip, read references/facebook-data-processing.md and
follow it exactly: unpack, delete all media leaving only raw JSON, fix the latin-1/UTF-8
mojibake, extract text, and SANITIZE - keep only content written by the user themselves
(confirm their exact Facebook display name first). Nothing from other people's comments
or messages may enter the corpus.
Phase 4 - Analyze
Run both analysis passes from the processing guide: scripted stylometrics (dash usage, emoji counts, exclamation rate, hashtags, openers, caps, lengths) and qualitative register reading of at least 15-20 long posts and 30-40 short ones. Confirm biography facts with the user before encoding them as guardrails - never encode unverified claims (service history, credentials, life events).
Phase 5 - Samples and approval
Draft sample posts in the user's voice: long form (500+ words), short form (under 3 sentences), and quick statements (8 words or less). Present them via AskUserQuestion for approval or tuning. Iterate until the user signs off. Only approved samples ship.
Phase 6 - Build and save the skill
Assemble the final skill using references/voice-skill-template.md: SKILL.md plus
references/fingerprint.md, anti-ai-rules.md, corpus.md, and samples/ split by type
(long-form.md, short-form.md, quick-statements.md). Save the skill to Claude Cowork
(package as .skill and present it with a Save skill button). Delete the raw export
data - it is private and does not belong in the shipped skill.
Quality bar
- Every fingerprint claim is grounded in counts or quotes from the real corpus.
- Every biography fact is user-confirmed. The guardrails list what must NEVER be claimed.
- The calibration test lives in the output skill: read it out loud - if it sounds like a press release it failed, if it sounds like the user it passed.
- The finished skill must produce writing that reads 100% human and never warrants a platform's AI-content label.