Brand Content Strategy
Published by puntorigen in avatar-skills
What this skill does
Turn a website or personal brand into a research-backed content + channel strategy. Profiles the site's positioning/credentials, discovers what reels rank in its niche (reel-discovery), filters out official/brand accounts to rank only real individual creators, reverse-engineers their cross-platform distribution playbook (perplexity_ask), and writes a positioning + 30-day content plan (with an optional AI-voice podcast layer wired to voice-clone + audio-theater). Use when the user wants to promot
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add this skill "brand-content-strategy" from https://github.com/puntorigen/avatar-skillsInstall with the CLI
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npx skills add https://github.com/puntorigen/avatar-skills --skill brand-content-strategySkill instructions
Brand Content Strategy
Turn a website / personal brand into a research-backed content + channel
strategy: what to post, where, for whom, and a 30-day plan to get known and
generate leads. It is an orchestration skill — it drives
reel-discovery, the perplexity_ask MCP, and the
avatar/audio pipeline (viral-video-script,
voice-clone,
avatar-reel-composer, and the
audio-theater skill) — and produces one markdown deliverable.
When to use
- "How do I get my site / brand known?" / "position me as an expert."
- "What kind of videos should I make? Who should I target?"
- "Build me a YouTube / TikTok / content strategy for
<domain>." - "Research what's working in my niche and turn it into a plan."
Inputs to gather (ask only what's missing)
| Input | Why |
|---|---|
| Website / domain (or brand name) | Profile positioning + credentials |
| Business goal | leads/consultancy vs audience vs sales — drives the funnel |
| Target geos + languages | e.g. US/Canada (EN) + Chile/LatAm (ES) → language arbitrage |
| Niche topics | seeds the discovery queries |
| Competitor handles (optional) | extra --business discovery |
Setup
- YouTube (recommended): set
YT_API_KEYfor exact counts — see reel-discovery. - TikTok/IG/Facebook (optional, robust): set
APIFY_TOKEN. - perplexity_ask MCP for the creator footprint research (step 5).
Workflow
- [ ] 1. Profile the brand (fetch the site → positioning, credentials, assets)
- [ ] 2. Design niches+geos (3-6 queries: core niche, broad authority, news, per language)
- [ ] 3. Discover (reel-discovery per query, --sort velocity)
- [ ] 4. Filter to humans (scripts/filter_creators.py → drop brands, rank people)
- [ ] 5. Reverse-engineer (perplexity_ask each top creator: footprint + funnel)
- [ ] 6. Synthesize (positioning, platforms, pillars, 30-day plan, funnel, audio)
- [ ] 7. Write deliverable (<brand>-30dias.md from the template in REFERENCE.md)
1. Profile the brand
Fetch the site (WebFetch). Extract the brand's positioning, credentials, proof points, products/services, and unfair advantages — these become the credential shortcut (see Principles). Also audit the site as the funnel destination: funnel coverage (top/mid/bottom), the existing CTA, locales/languages, and whether analytics exist — this seeds the website punch list (step 6).
2. Design niches + geos
Derive 3–6 discovery queries from the brand's niche. Cover, at minimum:
- the core niche (the brand's real differentiator),
- one broad authority term,
- one news / trend angle,
- the same core niche per target language (EN for US/CA, ES for LatAm…).
3. Discover
Run reel-discovery per query, sorted by velocity (what's breaking out now):
python3 .cursor/skills/reel-discovery/scripts/discover.py \
--topic "<query>" --platforms youtube,tiktok \
--sort velocity --since 120 --max-duration 240 \
--limit 25 --per-platform 12 --region US --lang en \
--slug <slug>
Repeat per language with --region/--lang (e.g. --region CL --lang es). Read
each discovery/<slug>/results.md for the "Cómo están publicados" section
(hashtags, sounds, channel sizes, captions) — that is the packaging playbook.
4. Filter to humans (exclude official/brand accounts)
Official product accounts (Claude, Kimi, Unity, monday…) are not competition. Collapse all discoveries into a ranked humans-only shortlist:
python3 .cursor/skills/brand-content-strategy/scripts/filter_creators.py \
--slugs <slug1>,<slug2> \
--keywords "agent,claude,coding,ia,automat,llm,cursor,codex" \
--min-views 8000 --sort velocity --top 30 \
--out discovery/_creators.md
It drops a default brand stoplist (extend with --exclude), ranks individuals by
views/day, and extracts links found in their descriptions (first read on their
footprint). Rank by velocity, not raw views — raw views favor mega media
channels and old hits.
5. Reverse-engineer the playbook
For the top ~6 individual creators (and the ES cluster), research their full
distribution with perplexity_ask. Use the prompt template in
REFERENCE.md → "Creator footprint prompt". Capture per creator:
platforms + followers, what they monetize, signature hook/format, and how they
repurpose across platforms. Flag unverifiable claims.
6. Synthesize the strategy
Combine the brand profile + publishing patterns + creator playbooks into: positioning, audience + platform priority, content pillars, hook/bio formulas, a 30-day calendar, the funnel + monetization ladder, a website punch list (P0/P1/P2 — always include it; see REFERENCE.md §9), metrics, the production pipeline, and (optional) the audio/podcast layer. Apply the Principles below.
7. Write the deliverable
Write <brand>-30dias.md using the full template in
REFERENCE.md → "30-day strategy template".
Principles (the reverse-engineered playbook)
Apply all — they are how the winners actually grow:
- Credential in the first second / bio (authority shortcut). Lead with the brand's strongest proof, not the product.
- Hook = result + number + tool, never the product first (e.g. "How I built [outcome in $/time] with [tool/agents]").
- Funnel architecture: short-form (TikTok/Reels/Shorts = discovery) → long-form (YouTube = proof + SEO) → link-in-bio → site.
- One asset → many surfaces. Produce once, distribute to all (and clip long-form into shorts). This repo's pipeline is that engine.
- Monetization ladder: free lead magnet/workshop → course/cohort → community → high-ticket consulting (the real back-end).
- Borrowed authority: guest on existing podcasts / press.
- Language arbitrage: an underserved language/region (e.g. Chile/LatAm in Spanish) is far easier to own than the saturated EN market.
Anti-patterns
- Ranking brands as competitors — always run
filter_creators.pyfirst. - Ranking by raw views for trend-spotting — use
velocity. - Pure AI-voice impersonation in a credibility brand — clone the person's own voice (voice-clone) and declare it; never fake a real guest's voice.
- Fully automated publishing with no human-in-the-loop — quality > volume.
- Inventing formats — steal proven ones (see viral-video-script).
- Treating the podcast as a discovery channel — it deepens/converts; clips and short-form do the discovery.
Outputs
discovery/<slug>/— raw reel-discovery research (gitignored).discovery/_creators.md+.json— humans-only ranked shortlist.<brand>-30dias.md— the strategy deliverable.
Utility scripts
| Script | Purpose |
|---|---|
scripts/filter_creators.py | Aggregate reel-discovery output, drop brand/official accounts, rank individual creators by velocity, extract their links |
Additional resources
- Brand-profiling checklist, query-design heuristics, the perplexity footprint prompt, the full distribution playbook, the 30-day template, and the audio / podcast layer: REFERENCE.md
Files included
- REFERENCE.md
- scripts/filter_creators.py
- SKILL.md

