Social seo
106 social media skills for AI agents - strategy, writing, video, design, platform growth, publishing, and analytics. Works with Claude, Cursor, OpenClaw, Hermes & 40+ agents.
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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," "TikTok SEO," "YouTube SEO," "keywords for social," "searchable captions," or wants search across platforms rather than just the feed. For single-platform depth, route "Instagram SEO" to instagram-seo and Pinterest asks to pinterest-seo; this skill owns the cross-platform framework. Reads brand-profile and audience first. All platforms are search engines; keywords, not hashtags, are the lever. Covers per-platform indexed surfaces, keyword research via autocomplete + native analytics (never fabricates volumes), the triple-mention technique, topical clusters, and the profile as a search asset. Routes hashtags to hashtag-strategy; hands the AI-search/LLM-citation (GEO) layer to ai-search-optimization. Measures via native search insights, not WoopSocial analytics.
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SKILL.md
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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:
- 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.
- Keywords, not hashtags, are the lever. Write for the search bar first; hashtags are a minor
category signal →
hashtag-strategy. - 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.
- 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 toai-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.instagram-seo,pinterest-seo— single-platform search depth (route platform-specific asks there).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.