Agent Skillscivitai/civitai › ecosystem-seo-page

ecosystem-seo-page

GitHub

为AI生成生态系(如Flux、SDXL)自动生成程序化SEO着陆页Mockup。通过解析代码常量自动提取模型信息,结合用户输入填充模板,旨在捕获高意图搜索流量并引导至生成器与会员体系。

.claude/skills/ecosystem-seo-page/SKILL.md civitai/civitai

Trigger Scenarios

需要生成特定AI模型的生态着陆页 创建用于SEO优化的Hub页面原型 为新模型家族添加宣传页面

Install

npx skills add civitai/civitai --skill ecosystem-seo-page -g -y
More Options

Non-standard path

npx skills add https://github.com/civitai/civitai/tree/main/.claude/skills/ecosystem-seo-page -g -y

Use without installing

npx skills use civitai/civitai@ecosystem-seo-page

指定 Agent (Claude Code)

npx skills add civitai/civitai --skill ecosystem-seo-page -a claude-code -g -y

安装 repo 全部 skill

npx skills add civitai/civitai --all -g -y

预览 repo 内 skill

npx skills add civitai/civitai --list

SKILL.md

Frontmatter
{
    "name": "ecosystem-seo-page",
    "description": "Generate a programmatic-SEO \"ecosystem hub page\" mockup for a Civitai generation ecosystem (Flux, SDXL, Pony, Illustrious, Wan, Qwen, etc.). Produces a self-contained, on-brand HTML landing page that ranks for \"<ecosystem> AI\", \"best <ecosystem> models\", \"<ecosystem> vs X\", \"how to run <ecosystem>\" and funnels visitors into the generator and membership. Auto-derives what it can from basemodel.constants.ts, asks the dev for the rest, optionally pulls live stats\/top-models, then publishes it as an artifact. Use when someone wants an ecosystem landing\/SEO page, a hub-page mockup, or to add a page for a new model family.",
    "allowed-tools": "Read, Write, Edit, Glob, Grep, AskUserQuestion, Artifact, Skill, Bash"
}

Ecosystem SEO Hub Page

Build one authoritative landing page per generation ecosystem. The strategy is programmatic SEO: a single template, populated per-ecosystem with data only Civitai has (models, LoRAs, real generations + prompts, usage metrics), that captures high-intent search ("best Flux models", "Flux vs SDXL", "how to run Wan") and funnels it into the generator and membership.

The visual design is frozen in template.html — it's Civitai's real dark-first system (card/badge/amber-bolt-CTA vocabulary). A fully-worked reference is example-flux.html. Your job is to fill the template with correct, real-as-possible content for the requested ecosystem — never to restyle it.

Workflow

1. Identify the ecosystem

Take it from the user's request (/ecosystem-seo-page Wan) or ask. Resolve it against src/shared/constants/basemodel.constants.ts — grep for the ECO.<Key> entry and its ecosystems/baseModelFamilies records.

2. Auto-derive everything you can (don't ask for these)

From basemodel.constants.ts and a quick grep of the repo, pull:

  • Display name (displayName) → {{ECO_NAME}}.
  • Modality → image / video / audio / 3D. Determines {{EXAMPLE_NOUN}} ("generations" vs "videos"), {{GEN_NOUN}} ("Images" vs "Videos"), the example labels, and whether the settings line needs length/fps. MODEL3D_ECOSYSTEM_IDS and the video-ecosystem list in the template comment are your guide.
  • Family / parent (parentEcosystemId, familyId) → informs positioning and which peers to compare against (siblings under the same family are natural comparison targets, e.g. Pony/Illustrious/NoobAI all under SDXL).
  • Open vs API-only → whether the "Run locally" card is real or should become an "API only, run it here" note.
  • Generation support — check the generation support entries and the generation graph/handler files to confirm the ecosystem is actually generatable and what the generator deep-link looks like (see step 5).

3. Ask the dev for what only a human knows

Use AskUserQuestion (batch the questions). Ask ONLY things you couldn't derive. Typical set:

  • Positioning — the one-paragraph "what is it / who made it / headline capability" hero intro. Offer a drafted option they can accept or edit.
  • Creator / attribution — e.g. "Black Forest Labs", license note for the badges and footer.
  • Comparison peers — which 3 ecosystems to put in the "vs" table (pre-fill a sensible default from the family, let them override).
  • Stats source — offer: (a) I'll query live counts (model count, generation count, LoRA count) via the postgres/clickhouse skills, or (b) use realistic placeholder numbers for a mockup. Default to asking because live queries touch prod.
  • Generator deep-link — confirm the URL shape that pre-selects this base model (and ideally a specific model/LoRA). This is the entire funnel; if it doesn't exist yet, flag it and use #.

Keep it to one AskUserQuestion round of 2–4 questions where possible. If the user said "just mock it up / use placeholders", skip straight to plausible placeholder data (mirror the Flux example's style) and note the assumptions in your summary.

4. Pull real data when asked (optional, prod-touching)

If the dev opts into live data:

  • Stats & top models — use the postgres-query skill (read-only) to count models per ecosystem and rank the top 6 by downloads/rating, and top LoRAs. Match on the ecosystem's base-model records.
  • Example generations — real image/prompt/settings triples are the highest-SEO section. Curated example images MUST be remixable: the "Remix" button feeds each into the generator, so only pick images whose generation metadata is present and not creator-hidden. Filter the selection query on i.type = 'image', i."nsfwLevel" BETWEEN 1 AND 1 (PG/SFW), i."needsReview" IS NULL, i."hideMeta" = false, and i.meta IS NOT NULL (ideally i.meta->>'prompt' IS NOT NULL). An image with hideMeta = true looks fine but opens an empty generator — never feature it. (The runtime service re-checks these and drops any that fail, but curate remixable IDs so all six render.)
  • Generation countsclickhouse-query skill if needed. Always keep these read-only and scoped; never block the mockup on them — fall back to placeholders.

4b. Write grounded unique content (overview + prompt tips + per-ecosystem FAQ) — the SEO differentiator

The real /ecosystems/[key] page carries three pieces of unique long-form text that are the primary SEO lever (depth + de-duplication). These MUST be grounded in authoritative sources — never free-written from model memory. Free-writing scales an accuracy risk across every page and reads as thin/duplicate content to search engines.

The EcosystemSeoConfig fields:

  • overview — 3 paragraphs of genuinely unique prose: what it is + provider + architecture/encoder, how its variants differ, and when to choose it vs. siblings. No superlatives stated as fact.
  • promptTips — 5 ecosystem-specific "how to prompt" bullets.
  • The cost FAQ must be ecosystem-specific, never a shared templated paragraph — an identical answer repeated across pages is a duplicate-content liability. Weave in something true about this model (lighter/cheaper → daily Blue Buzz stretches far; heavier → costs more Buzz).

Buzz honesty rule (applies to all copy): never claim generation is "free" or "runs free." It runs on Buzz; free users earn free Blue Buzz daily through on-site actions (reacting to images, etc.) — cheap models go far on it, pricier ones accumulate or need a membership. In the comparison table use "Available on Civitai" (not "Runs free on Civitai"). The only accurate "free" is "free Blue Buzz."

Two authoritative sources, both reachable from here:

  1. Model card → facts for the overview. The model's own description, in the DB, via postgres-query: SELECT id, name, left(regexp_replace(description,'<[^>]+>',' ','g'), 2500) AS desc FROM "Model" WHERE id IN (<featured checkpoint modelIds>)
  2. Prompt-enhancement guide → rules for promptTips. The orchestrator's canonical per-ecosystem guide. Extract ORCHESTRATOR_ENDPOINT + ORCHESTRATOR_ACCESS_TOKEN from .env (never print the token) and GET /v1/manager/prompt-analysis/{key}; the systemPrompt field holds the real rules (prompt style, token limits, weight-syntax + negative-prompt stance, camera/lighting/text conventions, known gotchas).
    • Watch for the generic fallback: some keys return boilerplate with no model-specific rules (seen for pony, illustrious, noobai). Detect it and fall back to the model card, and flag it.
    • Video ecosystems register per-variant keys — try several (wanvideo-25-t2v, ltxv23, …).

Rules: cite the exact sources used (modelId(s) + guide key + whether a real guide was found). Never invent numeric settings (CFG, steps, token limits) you can't source. If the model card and the guide conflict, prefer the guide and flag it for a human. This is independent, parallelizable work — one subagent per ecosystem scales it, but each MUST fetch both sources.

5. Fill the template

Copy template.html to docs/working/ecosystem-seo/<key>.html, then replace every {{TOKEN}} and expand each <!-- REPEAT --> block. Rules:

  • Keep the <style> block byte-for-byte. Only edit body content.
  • 6 model cards, 6 LoRA cards, 6 example cards, 5–6 FAQ items, 6–8 footer ecosystem links — match the reference counts.
  • Cycle placeholder gradient classes g1..g6 so the grids look alive.
  • Checkpoints use <span class="model-type-badge">; LoRAs add class lora.
  • Comparison table: {{ECO_NAME}} column carries class="col-primary"; wrap a winning cell in <span class="comparison-check">.
  • Video ecosystems: heading → "Example videos", labels → "Generated clip", settings include length/fps.
  • Write real microcopy, never lorem. Every FAQ answer ends in a soft CTA. The "how to run" right card must be honest about local requirements (or say API-only).
  • Update the <title> token and remove the top instructional HTML comment.

6. Publish

Call the Artifact tool on the filled file:

  • favicon: ⚡ (keep consistent across all ecosystem pages so they read as a set).
  • description: one line naming the ecosystem and that it's the SEO hub concept.
  • The file's own <title> names the artifact.

Then report to the dev: the artifact URL, what you auto-derived vs. asked vs. placeheld, and — importantly — whether the generator deep-link exists, since that's the funnel's linchpin.

Notes

  • This produces a mockup/concept, not a shipped route. If the dev wants it real, the follow-up is a Next.js /ecosystems/[key] page querying the same data — call that out but don't build it unless asked.
  • Placeholder images are intentional: the artifact CSP blocks remote image hosts, so gradient slots stand in for real on-site generations. Say so in the summary.
  • Don't invent metrics as if they're real when the dev didn't opt into live data — label them as illustrative.

Version History

  • 4214ecb Current 2026-08-20 18:49

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