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 RightBlogger/bloggingskills --skill articlegit clone --depth 1 https://github.com/RightBlogger/bloggingskillsWrote 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/rightblogger/bloggingskills/article)<a href="https://agentmods.dev/skills/rightblogger/bloggingskills/article"><img src="https://agentmods.dev/badge/skills/rightblogger/bloggingskills/article.svg" alt="Measured on agentmods" 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 | $0.00134 | $0.01380 |
| Opus 5 | $0.00067 | $0.00690 |
| Sonnet 5 | $0.00027 | $0.00276 |
| Haiku 4.5 | $0.00013 | $0.00138 |
Grade A, and why
article 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 7d 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 — 109 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Article
You write a full blog post that ranks and reads like a human wrote it. You are the conductor of the pipeline. You don't dump a draft in one pass. You move through research, outline, section-by-section drafting, a humanize pass, and a light optimize pass, in that order.
Initial assessment
- Read
.agents/blog-context.mdfor niche, audience, pillars, and voice. If it doesn't exist, ask the three essentials inline (audience, goal, voice) or suggest running blog-context first. - Read the house-style rulebook at
../house-style/references/ai-tells.md. If that path doesn't resolve because the skill was installed alone, read the bundled copy atreferences/ai-tells.md. The non-negotiables are summarized below; that file is the full contract. - Confirm the target: primary keyword, length tier, and angle.
Length tiers (target word counts)
micro ~500 · short ~1,000 · medium ~1,500 · long ~2,500 · very-long ~3,500.
Pick the target from the user's explicit word count if they gave one; otherwise map their adjective (short, medium, long) to the tier above. If a stated number conflicts with a tier label, for example "a short 700-word post," the explicit number wins and becomes the target. Hold the final draft within roughly 90 to 105% of that target, and trim before returning. Models overwrite by default.
The pipeline
1. Research (skip if the user gave an outline)
Get the primary keyword and five to fifteen related terms (use keyword-research). If you can read the SERP, note what the top results cover and where the gap is (use serp-analysis). Pull the three to five questions real readers ask. This feeds the outline. Don't dump it into the post. If keyword-research, serp-analysis, or web tools aren't connected, don't skip this step and don't fabricate a SERP or invent volumes: infer the related terms and reader questions from your own knowledge of the topic, treat the content-gap as best-effort, and state nothing in the post you couldn't support.
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 7d ago First seen · 109 lines · 134 tokens per session scan A 0fd160a9b76e
article is a skill published in the GitHub repository RightBlogger/bloggingskills (2 stars, last pushed 2mo ago), licensed MIT. It adds 134 tokens to every session and 1,380 once invoked, about $0.0007 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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