brand-content-strategy · git:20260709.ec45941 · 2026-07-09 · sha256 f111c9d17bbe9505
brand-content-strategy git:20260709.ec45941A
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--- name: brand-content-strategy description: 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 promote/grow a website, get known, position themselves as an expert/authority, decide what videos to make, launch a YouTube/TikTok/Instagram channel, find a target audience, or build a content/creator strategy for a domain or brand. --- # 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`](../reel-discovery/SKILL.md), the `perplexity_ask` MCP, and the avatar/audio pipeline ([`viral-video-script`](../viral-video-script/SKILL.md), [`voice-clone`](../voice-clone/SKILL.md), [`avatar-reel-composer`](../avatar-reel-composer/SKILL.md), 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_KEY` for 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*): ```bash 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: ```bash 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](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](REFERENCE.md) → "30-day strategy template". ## Principles (the reverse-engineered playbook) Apply all — they are how the winners actually grow: 1. **Credential in the first second / bio** (authority shortcut). Lead with the brand's strongest proof, not the product. 2. **Hook = result + number + tool**, never the product first (e.g. "How I built [outcome in $/time] with [tool/agents]"). 3. **Funnel architecture:** short-form (TikTok/Reels/Shorts = discovery) → long-form (YouTube = proof + SEO) → link-in-bio → site. 4. **One asset → many surfaces.** Produce once, distribute to all (and clip long-form into shorts). This repo's pipeline *is* that engine. 5. **Monetization ladder:** free lead magnet/workshop → course/cohort → community → high-ticket consulting (the real back-end). 6. **Borrowed authority:** guest on existing podcasts / press. 7. **Language arbitrage:** an underserved language/region (e.g. Chile/LatAm in Spanish) is far easier to own than the saturated EN market. ## Anti-patterns 1. **Ranking brands as competitors** — always run `filter_creators.py` first. 2. **Ranking by raw views** for trend-spotting — use `velocity`. 3. **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. 4. **Fully automated publishing** with no human-in-the-loop — quality > volume. 5. **Inventing formats** — steal proven ones (see viral-video-script). 6. **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](REFERENCE.md)