Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add T4wroot/agentic-seo --skill use-casesgit clone --depth 1 https://github.com/T4wroot/agentic-seoWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/t4wroot/agentic-seo/use-cases)<a href="https://agentmods.dev/skills/t4wroot/agentic-seo/use-cases"><img src="https://agentmods.dev/badge/skills/t4wroot/agentic-seo/use-cases/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/t4wroot/agentic-seo/use-cases"><img src="https://agentmods.dev/badge/skills/t4wroot/agentic-seo/use-cases.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00076 | $0.01305 |
| Opus 5 | $0.00038 | $0.00652 |
| Sonnet 5 | $0.00015 | $0.00261 |
| Haiku 4.5 | $0.00008 | $0.00130 |
Grade A, and why
use-cases-page-generator scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to use-cases-page-generator — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 115 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pages: Use Cases
Guides use case pages that bridge product features and real-world customer problems. Scenario-first is the primary organization. BOFU (bottom-of-funnel) pages for SaaS/B2B. Answer "when would I use it?" and "how does it help me?" — distinct from solutions (industry/outcome).
When invoking: On first use, if helpful, open with 1–2 sentences on what this skill covers and why it matters, then provide the main output. On subsequent use or when the user asks to skip, go directly to the main output.
Initial Assessment
Check for project context first: If .claude/project-context.md or .cursor/project-context.md exists, read it for product, ICP, and proof points.
Identify:
- Scenarios: Concrete situations (event marketing, lead nurturing)
- Personas: Roles (Marketer, Sales Rep, Realtor)
- Business goals: Acquisition, Retention, Upsell
- Format: Single page vs. per-use-case pages; standalone or under solutions
- Primary goal: Demo, sign up, contact sales
Use Case Page Structure
| Section | Purpose |
|---|---|
| Headline | "When you need to X, we help you Y" or "For [role]: solve X" |
| Problem | Pain points, day-to-day challenges |
| Solution | How product addresses them; link to relevant features (do not duplicate feature copy) |
| Proof | Case study, testimonial, metrics |
| CTA | Try free, book demo, contact |
| Related | Link to other use cases, parent solution |
Best Practices
Scenario-First
- Concrete situations: "When you need to run event marketing at scale..."
- Before-after: Show transformation, not just features
- One scenario per page: Don't mix "event marketing" and "lead nurturing"
Content Differentiation (vs Features)
- Use case = scenario + problem + outcome: Write the story (when, who, why, result); reference features via links.
- Do not duplicate feature copy: Avoid repeating capability lists or benefit bullets from the features page; instead, describe how the product solves this scenario and link to /features for details.
- Avoid content cannibalization: Each use case page targets a unique scenario intent; overlap with features (both Commercial/Consideration) dilutes SEO — differentiate by content angle (scenario vs capability).
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 6d ago First seen · 115 lines · 76 tokens per session scan A 7836c6150533
use-cases-page-generator is a skill published in the GitHub repository T4wroot/agentic-seo (15 stars, last pushed 7d ago), licensed MIT. It adds 76 tokens to every session and 1,305 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to use-cases-page-generator, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
fire-your-seo-agency
A procedure for improving how a website appears in search engines and how AI answer systems find and cite it. It covers search, answer-engine, generative-AI, and Naver visibility.
content-thicken
Evidence-driven blog driver. Takes ONE target from the fused search plus AI-answer content library, pulls the real questions it has to answer, drafts a thick long-form guide against a template contract, validates it deterministically, and stops at preview. Two modes, thicken an already-earning post IN PLACE (never…
backlink-outreach
Find, evaluate, pitch and track natural backlink and content partnerships. Prospects come from the GEO citation data rather than a generic blog search: the targets are the pages an AI already cites when answering your category questions. Research runs on the Monid tool layer (web search and scrape, authority metrics…
geo-monitor
Run and read the GEO pipeline, which measures whether AI answer engines mention, recommend and cite your site. Puts a fixed registry of real user questions to an answer engine through the Monid tool layer, detects the three signals plus competitors, and turns "a rival is named and we are not" into a tracked work…
seo-intake
Run and read the SEO intake pipeline. Pulls the organic keyword set for your domain and for each competitor through the Monid tool layer, computes the gap locally, and routes every keyword to the one action that can help it (write-new / striking / build-depth / defend / noise). Use when asked to refresh the SEO queue…
bing-duplicate-content-fix
Audit article groups, WordPress categories, or supplied URLs for copied content, near-duplicate templates, search-intent overlap, and keyword cannibalization; prepare exact SEO/AEO/GEO fixes; apply only approved WordPress changes; verify saved and public results; and request a Bing recrawl when authorized. Use for…