Run a full Section 508 + WCAG 2.2 Level AA accessibility audit on a federal / .gov / public-sector website or ICT product. Triggers: "Section 508", "508 audit", "WCAG", "VPAT", "ACR".
日本語の概要は準備中です。原文の説明を表示しています。
Generate a 2026-grade content brief for a target query — combines classic SERP analysis with AI Overview / Perplexity / ChatGPT citation analysis, entity recommendations (target ≥15 recognized entities), topical authority gap map, intent-mapped heading structure, internal linking targets.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
You generate a content brief that ranks AND gets cited by AI. Modern briefs are no longer "keyword + word count + headings." They are entity-aware, intent-mapped, E-E-A-T-aware, and AI-citation-targeted.
Why this differs from a 2023-era brief:
Verify:
Recovery:
For the target query, gather signals from THREE surfaces:
Output brief/01_competitive_landscape.md with side-by-side citation tables.
VALIDATION: Per-engine citation list has ≥ 3 URLs. Overlap with organic top-10 noted.
FALLBACK: Without Perplexity/ChatGPT API access, capture manually via the user's browser (provide them a copy-paste prompt). Less precise but unblocks the brief.
From the top 10 organic + AI-cited sources, extract every recognized entity (proper noun mapped to a Knowledge Graph node).
Bucket entities by type:
Output brief/02_entities.md ranked by co-occurrence frequency across sources.
Identify:
VALIDATION: Entity list has ≥ 25 candidates. Must-mention list has ≥ 10 entities.
Generate the H2/H3 outline. Each heading is a question the reader (or AI engine) is trying to answer.
Default outline patterns by intent:
Informational ("what is X", "how does X work"):
Commercial-investigation ("best X", "X vs Y", "X review"):
Transactional ("buy X", "X pricing", "X near me"):
Output brief/03_outline.md.
VALIDATION: Outline is intent-matched. Each H2 maps to a specific user question or buyer-journey stage.
Compile the FAQ section from multiple sources:
Dedupe, rank by frequency, output as a 5–10 question FAQ section with answer drafts (1–3 sentences each).
VALIDATION: FAQ has ≥ 5 questions, each with a draft answer ≤ 60 words.
From the user's existing top pages, identify:
Format each as:
- [{Anchor text}](https://example.com/path) — Why: {one-sentence rationale}
VALIDATION: Each suggested link has a specific anchor text and rationale, not just a URL.
FALLBACK: Without site access, suggest internal-link templates ("link to your pillar page on {X} topic") and let the writer fill specifics.
Specify what makes this content citable, not just rankable:
/author/{slug}, Person schema, ≥ 3 sameAs.dateModified schema and visible "Updated YYYY-MM-DD" in DOM.Mark each as REQUIRED or RECOMMENDED based on competitiveness of the query (high-competition → all REQUIRED).
VALIDATION: List is specific to this brief's topic, not generic boilerplate.
Combine all phases into brief/{slug}.md:
# Content Brief — {Target Query}
**Generated:** {date}
**Intent:** {informational / commercial-investigation / transactional}
**Target length:** {word count based on competitor median ±10%}
**Author requirement:** {Person entity profile complete: yes/no — must be yes to publish}
## TL;DR for the writer
- Lead with the direct answer in the first 60 words.
- Cover these MUST-MENTION entities: {list of 10}
- Hit ≥ 15 total recognized entities (see entities.md for the full pool).
- Internal-link to: {3 pages}
- FAQ section is required (5+ questions from FAQ.md).
- Author must be {Name}; if not, set up the Person entity first.
## Outline
{from Phase 3}
## Entities to include
{from Phase 2, must-mention bucket}
## FAQ section
{from Phase 4}
## Internal Linking
{from Phase 5}
## E-E-A-T requirements
{from Phase 6}
## Competitor benchmarks
- Median word count: {N}
- Median entity count: {N}
- Median schema types: {Article, FAQPage, ...}
## Schema to ship with the page
- Article (required)
- FAQPage (if FAQ section is present)
- BreadcrumbList
- {anything else specific to this topic — HowTo, Product, etc.}
VALIDATION: Brief is ≤ 6 pages of markdown. A competent writer should be able to produce the article from the brief alone without further research.
FALLBACK: If brief is too thin (insufficient SERP signal — emerging topic), say so explicitly and recommend supplementing with subject-matter-expert interview.
Score 1–5:
Common gap: brief loses entity discipline at writing time. Cap the brief by reminding the writer in the TL;DR to count entities before publishing.
Append to ~/.claude/skills/seo-content-brief/LEARNINGS.md:
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Run a full Section 508 + WCAG 2.2 Level AA accessibility audit on a federal / .gov / public-sector website or ICT product. Triggers: "Section 508", "508 audit", "WCAG", "VPAT", "ACR".
日本語の概要は準備中です。原文の説明を表示しています。
Analyzes actuarial modeling systems for loss reserving accuracy, premium pricing methodology, mortality/morbidity tables, stochastic modeling, and capital adequacy per SOA and Solvency II standards..
日本語の概要は準備中です。原文の説明を表示しています。
Analyzes advertising yield across programmatic and direct-sold inventory including CPM/CPC/CPA performance, header bidding efficiency, fill rate optimization, inventory monetization strategies, and compliance with IAB standards and OpenRTB protocols..
日本語の概要は準備中です。原文の説明を表示しています。
Create and manage Architecture Decision Records using the Michael Nygard format. Triggers: you need to document architecture decisions, record technical choices, explain why a technology was chosen.
日本語の概要は準備中です。原文の説明を表示しています。
Analyzes affordable housing management software for unit allocation algorithms, waitlist management, income verification workflows, Fair Housing compliance, LIHTC and Section 8 program tracking, inspection scheduling, and tenant reporting..
日本語の概要は準備中です。原文の説明を表示しています。
Rewrites existing landing pages, blog posts, and documentation so AI search engines (Google AI Overviews, ChatGPT, Perplexity, Claude, Gemini) cite them. Triggers: an existing page underperforms in AI answers despite ranking well in classic SERPs.
日本語の概要は準備中です。原文の説明を表示しています。