---
name: combined-voice-creator
license: AGPL-3.0-or-later
description: "Build a personal writing-voice skill from Littlebird history and a Facebook export. Use when both consented sources are available. Read README.md for the guide map."
metadata:
  hive-tier: standalone
  version: "1.0.0"
  author: "Mario Aldayuz / Littlebird"
---

# Combined Voice Creator

Start with [README.md](README.md) for the workflow map and detailed references.

Build the deepest possible personal voice skill by fusing two corpora:

- **Littlebird** supplies recent captured writing, sent messages, spoken meeting
  patterns, and rich background context about who the user is.
- **Facebook export** supplies months of public-facing writing across every register -
  long rants, quick jokes, comments, DMs.

Together they cover both halves of a person's voice: how they write in public and how
they talk when nobody's performing. The output is a skill structured like
`mario-aldayuz-voice`: lean SKILL.md + fingerprint + anti-AI rules + verbatim corpus +
approved samples.

## Phase 0 - Source check

Ask via AskUserQuestion (multiSelect): "Which sources can we mine?"
1. **Both Littlebird and Facebook (Recommended)** - the full pipeline below.
2. Littlebird only - hand off to the littlebird-voice-creator flow.
3. Facebook only - hand off to the facebook-voice-creator flow.

## Phase 1 - Kick off BOTH tracks in parallel

Start the Facebook export FIRST because it has a 2-3 hour wait baked in, then mine
Littlebird while Facebook builds the archive.

### Track A: Facebook export (start immediately)

Follow `references/facebook-export-guide.md` step by step with the screenshots in
`assets/`. Confirm via AskUserQuestion: Posts (required) + Messages (optional) +
Profile information (optional); Date range 6 months or 1 year; Format JSON; Media
quality Lower. Then the user waits 2-3 hours for Facebook (4-day download window).

### Track B: Littlebird mining (while waiting)

Follow `references/littlebird-mining-guide.md`:
1. Verify Littlebird is installed with 1-2 weeks of data (install links, code
   E6GP4BQE for two months free, if they're new - then pause this track).
2. Verify the Littlebird MCP is connected (`https://mcp.littlebird.ai/mcp`, docs at
   https://support.littlebird.ai/docs/mcp/). List tools, use real names.
3. Run multiple targeted retrievals across registers plus background-context queries.
4. Obey the attribution guardrail - viewed is not written.
5. CRITICAL: confirm every retrieved fact with the user via AskUserQuestion, then purge
   everything erroneous. Unconfirmed facts do not ship.

## Phase 2 - Process the Facebook zip

When the export lands, follow `references/facebook-data-processing.md`: unpack, delete
all media leaving raw JSON, fix the latin-1/UTF-8 mojibake, extract, and sanitize to
ONLY the user's own words (confirm their Facebook display name first).

## Phase 3 - Merge and analyze

Merge both corpora with source tags, dedupe (Littlebird may have captured the same
Facebook posts), then run both analysis passes from the processing guide:

- Scripted stylometrics over the merged corpus (dashes, ellipses, emoji counts,
  exclamation rate, hashtags, openers, caps, length distribution).
- Qualitative register reading (15-20 long pieces, 30-40 short ones minimum).
- Where the sources disagree, weight the LARGER and MORE RECENT sample, and note
  register differences (public post voice vs DM voice vs spoken voice) explicitly in
  the fingerprint.
- Biography guardrails come from Littlebird background mining plus Facebook profile
  info, and every fact gets user-confirmed before encoding. List what must NEVER be
  claimed.

## Phase 4 - Samples and approval

Draft samples across the user's registers: long form (500+ words), short form (under 3
sentences), quick statements (8 words or less). Present batches via AskUserQuestion for
approval or tuning. Iterate until they match. Only approved samples ship, committed to
`references/samples/` by type (long-form.md, short-form.md, quick-statements.md).

## Phase 5 - Build and save

Assemble per `references/voice-skill-template.md` (the guide-reference-sample-research
method): SKILL.md + references/fingerprint.md + anti-ai-rules.md + corpus.md +
samples/. Package as a .skill and save to Claude Cowork. Delete all raw export and
mined data from the working area - private data does not ship.

## Quality bar

- Real data or nothing. No fabricated corpus, ever.
- Every fact user-confirmed; every fingerprint claim grounded in counts or quotes.
- One register per generated piece; rhythm imitated, not just vocabulary.
- Output must read 100% human - it should never warrant a platform's AI-content label.
  Read it out loud: press release = fail, the actual person = pass.