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 dazz/kostja94-marketing-skills --skill article-page-generatorgit clone --depth 1 https://github.com/dazz/kostja94-marketing-skillsWrote 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/dazz/kostja94-marketing-skills/article-page-generator)<a href="https://agentmods.dev/skills/dazz/kostja94-marketing-skills/article-page-generator"><img src="https://agentmods.dev/badge/skills/dazz/kostja94-marketing-skills/article-page-generator/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/dazz/kostja94-marketing-skills/article-page-generator"><img src="https://agentmods.dev/badge/skills/dazz/kostja94-marketing-skills/article-page-generator.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 | $0.00111 | $0.03754 |
| Opus 5 | $0.00056 | $0.01877 |
| Sonnet 5 | $0.00022 | $0.00751 |
| Haiku 4.5 | $0.00011 | $0.00375 |
Grade A, and why
article-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 11d 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.
How it starts
The opening of the file, as written. The whole thing — 278 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pages: Article (Single Post)
Guides structure, SEO, and UX for individual article pages — layout, metadata, schema, technical. For article body content (intro, body, conclusion, writing), see article-content. Distinct from blog-page-generator, which covers the blog index/listing page.
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.
Output workflow: Always output in order: 0. Research Phase (keywords, search intent, competitors) → 1. Intent Analysis → 2. Content Analysis → 3. Recommendations. Do not skip steps. When Research Phase was performed via web search, show the search results and findings.
Optimization Foundation: Four Inputs
Article analysis and creation rest on four inputs. Gather or infer them before outputting recommendations:
| Input | Purpose | Source |
|---|---|---|
| Product | Product connection, features, use cases, CTA placement | project-context (Sections 1–4, 9–11); article content; web search |
| Keywords | Target keyword, primary/secondary placement | project-context Section 6; keyword-research; article |
| Article intent | Informational, commercial, transactional, navigational; drives structure, CTA, SEO depth | project-context Section 6 (target intent); article orientation; content type |
| Competitor articles | Structure to adopt, content gaps, length target, keyword opportunities | User-provided URLs; project-context Section 11; web search |
When any input is missing: Proactively ask or search. For article analysis: perform Research Phase (keyword search, search intent, competitor articles) by default — see Research Phase section. For product/keywords/intent, infer from article or prompt user to add project-context.
Before Analysis: Gather Context
1. Product / company context
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.
- 11d ago First seen · 278 lines · 111 tokens per session scan A 36098e7ca47e
article-page-generator is a skill published in the GitHub repository dazz/kostja94-marketing-skills (2 stars, last pushed 2mo ago), licensed MIT. It adds 111 tokens to every session and 3,754 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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