菜单
Use when analyzing topical authority, clustering a domain's ranked keywords, finding strong, building, weak, and missing topics against organic competitors, calculating a 0-100 Content Score, or recommending five articles with DataForSEO MCP evidence.
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Use when analyzing one webpage's primary topic, finding DataForSEO-backed keyword opportunities, or producing evidence-based search, Open Graph, and Twitter metadata in a Markdown report.
Use when creating or maintaining a persistent SEO keyword watchlist, discovering ranked domain keywords, checking Google positions across runs, comparing gains and losses, listing or removing tracked entries, or producing a ranking-change report.
Use when consolidating dated SEO reports for one domain into a concise full SEO report, prioritizing critical next actions, or surfacing cross-analysis ranking opportunities from files under SEO/<domain>/ with a current DataForSEO MCP validation snapshot.
Use when auditing one webpage for technical SEO, indexability, links, metadata, structured data, or desktop/mobile rendering and performance, then producing a prioritized report with DataForSEO-derived Technical Scores.
Use when performing SEO analysis with the DataForSEO MCP, selecting or sequencing DataForSEO tools, interpreting their responses, estimating request scope, troubleshooting calls, or explaining the MCP and underlying API contracts.
Use when detecting pages competing for the same keywords, selecting canonical target pages, deciding whether to merge, redirect, canonicalize, differentiate, or retain overlapping content, or recommending evidence-based internal links with DataForSEO MCP.
| name | seo-content-suggestions |
| description | Use when analyzing topical authority, clustering a domain's ranked keywords, finding strong, building, weak, and missing topics against organic competitors, calculating a 0-100 Content Score, or recommending five articles with DataForSEO MCP evidence. |
| compatibility | Requires the official DataForSEO MCP server with the DATAFORSEO_LABS module enabled and filesystem write access. |
Use Ranked Keywords, Competitors Domain, and Domain Intersection.
Require a target domain; if absent, ask and wait. Normalize a hostname or HTTP(S) URL to lowercase without credentials, port, suffix, trailing dot, or leading www.; reject malformed input. Accept up to five competitors. Default to United States/en; disclose assumptions. Use Google organic and ignore_synonyms: true. Ask before retries, pagination, or extras.
dataforseo_labs_google_ranked_keywords for target with limit: 200, organic items, descending volume. Retain keyword, rank_group, URL, ETV, volume, difficulty, and intent.dataforseo_labs_google_competitors_domain. Exclude target and top domains; retain five by intersections, then organic ETV.dataforseo_labs_google_domain_intersection with target1: competitor, target2: target, intersections: false, organic items, and limit: 200. Deduplicate keywords, retaining competitors.limit: 200 for the first/top competitor. Use median non-null rank_info.main_domain_rank as benchmark.Log each call's endpoint and top-level cost USD. Sum unrounded values. Scope: Total cost: x,xx USD (decimal comma, two digits). Include zero; missing cost means incomplete subtotal; name affected calls.
Normalize case/punctuation and singularize; group by stems, head terms, and meaning. Merge synonyms; split differing intent/audience. Aim for 8-15 clusters.
Classify target and gap clusters in order:
Report count, best/average position, top-10 count, ETV, volume, URLs, competitor coverage, and status per cluster.
total_clusters includes all clusters. From top ceil(n/4) target keywords by volume calculate:
avg_position_top_quartile_score = clamp((100 - mean_rank_group) / 99, 0, 1)
content_score = round(50 * strong_clusters/total_clusters + 25 * (1 - missing_clusters/total_clusters) + 25 * avg_position_top_quartile_score)
If clusters or positions are absent, report unavailable.
Select from Missing and Building clusters. Prioritize commercial or transactional keywords with volume above 200 and difficulty below benchmark; break ties by volume, lower difficulty, then related-term breadth. If fewer than five qualify, use nearest candidates and label relaxed conditions.
Provide title, target and related keywords, intent, volume, difficulty, benchmark, status, rationale, and word-count estimate.
Write Markdown with Scope and total cost, summary, score inputs, competitors, cluster matrix, briefs, gaps, limitations, content moves, and call log. Start with local ISO date.
Use the requested root or SEO/; create <root>/<domain>/. Save as <YYYY-MM-DD>_Content-Suggestions_<domain>.md, for example 2026-06-19_Content-Suggestions_example.com.md.