--- name: social-seo description: >- Use to make social content discoverable through SEARCH across social platforms — the social-SEO / keyword-discovery skill. Run when the user says "social SEO," "get found in search," "rank on TikTok/YouTube/Pinterest search," "Instagram SEO," "keywords for social," "searchable captions," "evergreen discovery," or wants to be found when people search rather than just appear in the feed. Reads brand-profile and audience first. Built on the 2026 reality: all social platforms are search engines (TikTok/IG/YouTube/Pinterest/LinkedIn), keywords (not hashtags) are the discovery lever, search optimization doubles as recommendation categorization, and social content also surfaces on Google. Covers what each platform indexes (spoken audio/transcription, on-screen text, captions, titles/descriptions, alt text, profile/name fields), keyword research using platform autocomplete and native search analytics (never fabricates search volumes), the triple-mention technique, topical clusters for evergreen discovery, and the profile as a search asset. Routes to hashtag-strategy (hashtags as a minor signal), caption-writer, profile-optimization, and the growth skills; hands the AI-search/LLM-citation (GEO) layer to ai-search-optimization. Judges via native platform search insights — not WoopSocial analytics. metadata: version: 1.0.0 license: MIT --- # Social SEO Make content **findable when people search**, not just visible when the feed happens to show it. In 2026 every social platform is a search engine, and search is the highest-intent, most **evergreen** discovery there is. Four truths shape everything: 1. **All social platforms are search engines** (TikTok/IG/YouTube/Pinterest/LinkedIn) — and people search *different* platforms for different intents. If you only optimize for the feed, you're invisible to people actively looking. 2. **Keywords, not hashtags, are the lever.** Write for the search bar first; hashtags are a minor category signal → `hashtag-strategy`. 3. **Search optimization doubles as recommendation optimization** — the keywords that get you found in search are the same signals the algorithm uses to categorize you for the right feed/FYP audience. 4. **SEO turns posts into evergreen assets** — a search-optimized post keeps getting found for months; a feed post dies in ~48h. (Full model + the AI-search/GEO boundary: `references/why-social-search.md`.) ## Step 0 — Read the foundation + the goal Load `brand-profile.md` and `audience.md` (their exact search language matters). Get the **platform(s)** and what the user wants to be **found for**. ## Step 1 — Keyword research (real demand, never invented) Find the terms people actually search via **platform autocomplete**, **"others searched for"**, related searches, **comments**, audience language, and the user's **native search analytics** (+ tools like TikTok Creative Center / VidIQ). **The agent can't pull live search volumes — never fabricate numbers**; give the method and work from intent/specificity. Favor long-tail, intent-rich queries you can genuinely answer. See `references/keyword-research-and-technique.md`. ## Step 2 — Place keywords across the platform's SEO surface Each platform indexes different things — optimize the right ones (full per-platform guide in `references/platform-seo-surfaces.md`): - **TikTok** — spoken audio (transcribed) + on-screen text + caption (the **triple mention**). - **Instagram** — caption + the **searchable name/display field** + bio + alt text + captioned Reels. - **YouTube** — keyword-led **title** + ~200–300w **description** + **transcript/captions** + chapters. - **Pinterest** — keyword **title + description + board names + alt** (hashtags deprecated there). - **LinkedIn** — searchable **headline/About** + on-topic post keywords → `linkedin-growth`. - **Cross-cutting** — subtitles, alt text, descriptive file names, a consistent branded handle. ## Step 3 — The on-content technique **Lead with keywords, support with hashtags.** State the primary phrase in **natural language, early, once or twice**; align audio + on-screen + caption to **one** search intent; add 3–5 niche hashtags. **Never keyword-stuff** (spam dilutes your topical signal). Resolve the search-vs-feed tension (clarity vs hook) deliberately. See `references/keyword-research-and-technique.md`. ## Step 4 — Build topical clusters (evergreen authority) One post rarely owns a query. **Cluster** evergreen content around a pillar topic so you become the **answer/authority** — which compounds *and* sharpens recommendation categorization. Map a `content-pillars` pillar → a keyword cluster → many evergreen posts. ## Step 5 — Optimize the profile as a search asset The **name/display field, handle, headline/bio** should carry the searchable keyword/category (not just a clever brand line). This is the *searchability* lens — `profile-optimization` owns the *conversion* lens; both matter. Public profiles/content are increasingly **Google-indexable** too. ## Step 6 — Measure (honestly) + hand off GEO Track **discoverability**: impressions from search, the search terms that found you, profile visits from non-followers, saves, evergreen-post growth — via **native platform search analytics** (+ Search Console/UTMs). **No WoopSocial analytics.** For getting cited by **AI search/LLMs (GEO)**, hand off to `ai-search-optimization` — related but separate. ## Orchestration map social-seo sets the discovery layer; it routes to / is routed from: `hashtag-strategy` (hashtag specifics) · `caption-writer` (adds the keyword layer) · `profile-optimization` (conversion lens) · `content-pillars` (clusters) · `tiktok-growth` / `instagram-growth` / `linkedin-growth` (search as a growth pillar) · `ai-search-optimization` (GEO hand-off) · `scheduling-and-queue` (publish). ## Quality bar — self-check - Did I do **real keyword research** (autocomplete/native analytics) and **avoid inventing volumes**? - Did I optimize the **platform-specific indexed surfaces** (not one generic answer)? - Did I use **lead-with-keywords + the triple mention**, in **natural language** (no stuffing)? - Did I think in **evergreen clusters / topical authority**, and note the **search = recommendation** payoff? - Did I treat the **profile as a search asset**, route hashtags to `hashtag-strategy`, and **hand GEO** to `ai-search-optimization`? - **Native-search-insights** measurement, **no WoopSocial analytics**, **searchability not guaranteed rankings**? ## Edge cases & pushback - **"Give me exact search volumes"** → can't pull live volume; show the research method; don't fabricate. - **"Stuff every keyword + 30 hashtags"** → refuse; spam dilutes the signal; natural language + a few niche tags. - **"I optimized one post, done"** → build a cluster; one post rarely owns a query. - **"Just use trending hashtags"** → hashtags categorize, keywords get found → `hashtag-strategy`. - **"Make ChatGPT/Google-AI cite me"** → that's GEO → `ai-search-optimization`. - **"Which post ranks best?"** → native platform search insights; no WoopSocial analytics. - **Clever-but-vague title** → keep the searchable phrase; add intrigue after the keyword. ## Related skills - `brand-profile`, `audience-research` — the search language and positioning. - `hashtag-strategy` — the hashtag layer (a minor signal); `caption-writer` — caption craft. - `profile-optimization` — profile as conversion (this skill = profile as search). - `content-pillars` — pillars become keyword clusters; the growth skills lean on search. - `ai-search-optimization` — the AI-search/LLM-citation (GEO) hand-off; `scheduling-and-queue` — publish. ## References - `references/why-social-search.md` — the 2026 reality, the three layers, search=recommendation, evergreen, the GEO boundary. - `references/platform-seo-surfaces.md` — what each platform indexes and how to optimize it (TikTok/IG/YouTube/Pinterest/LinkedIn/X/FB + cross-cutting). - `references/keyword-research-and-technique.md` — finding keywords (no fabrication), the triple-mention technique, clusters, no-stuffing, measurement. - `references/examples.md` — worked optimizations per platform + a cluster plan + honest scope.