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 agentmods add skills/affitor/affiliate-skills/create-skillnpx skills add Affitor/affiliate-skills --skill create-skillgit clone --depth 1 https://github.com/Affitor/affiliate-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/affitor/affiliate-skills/create-skill)<a href="https://agentmods.dev/skills/affitor/affiliate-skills/create-skill"><img src="https://agentmods.dev/badge/skills/affitor/affiliate-skills/create-skill.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 | $0.00129 | $0.04143 |
| Opus 5 | $0.00064 | $0.02072 |
| Sonnet 5 | $0.00026 | $0.00829 |
| Haiku 4.5 | $0.00013 | $0.00414 |
Grade A, and why
create-skill 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- create-skill — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 437 lines — stays where its author put it; the contents beside it link to each section on GitHub.
List Affitor Skill
Turn a repeatable AI prompt or workflow into a structured, shareable skill for the
affiliate-skills GitHub repository.
The output is a complete SKILL.md file that works in any AI agent — shared via
npx skills add Affitor/affiliate-skills so anyone can install it.
Stage
This skill belongs to Stage S8: Meta
When to Use
- User has a prompt they keep reusing and wants to turn it into a shareable skill
- User wants to create a new skill for the affiliate-skills repository
- User wants to write a SKILL.md file in the standard format
- User says "make this a skill" or "write a skill for X"
- User wants to package an AI workflow so others can replicate it
Input Schema
{
raw_prompt: string # (required) The prompt, workflow description, or detailed explanation of what the skill does
failure_modes: string # (optional) What goes wrong when the output is bad — helps write better Instructions and Error Handling
niche: string # (optional) Category hint, e.g., "content", "research", "seo"
examples: string # (optional) Example input/output pairs the user already has
}
Workflow
Step 1: Understand What the Prompt Actually Does
Before writing anything, analyze the user's raw prompt or workflow description:
- Task type — Is this content creation, research, analysis, planning, automation, or something else?
- Variable inputs — What changes each time? (product name, URL, audience, topic, etc.)
- Fixed structure — What stays the same? (output format, sections, tone, constraints)
- Quality differentiator — What makes a good output vs. a bad one?
- Failure modes — Where does the AI tend to go wrong without explicit guidance?
If the user gave a vague description instead of an actual prompt, ask:
- "What do you typically paste into ChatGPT/Claude for this?"
- "What does the output look like when it works well?"
- "What goes wrong when it doesn't?"
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 · 437 lines · 129 tokens per session scan A 43f40d822c59
create-skill is a skill published in the GitHub repository Affitor/affiliate-skills (646 stars, last pushed 2mo ago), licensed MIT. It adds 129 tokens to every session and 4,143 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 2026-08-30.
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list-affitor-skill
Turn a repeatable AI prompt or workflow into a structured, publish-ready skill for list.affitor.com. Use this skill when the user wants to create a new skill, write a SKILL.md, convert a prompt to a skill, publish a skill to the directory, or document an AI workflow. Also trigger for: "create a skill", "write a…
create-skill
Turn a repeatable AI prompt or workflow into a structured, shareable skill for the affiliate-skills GitHub repository. Use this skill when the user wants to create a new skill, write a SKILL.md, convert a prompt to a skill, share a skill via the GitHub repo, or document an AI workflow. Also trigger for: "create a…
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recon-playbook
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im-human
台灣繁體中文與英文的語態控制與去 AI 味編輯技能,兩種模式。語態模式:使用者說「我是人」「開啟我是人」「說人話模式」或要 Claude「用我是人講話」時啟動,之後 Claude 自己的每一句輸出都改用台灣人日常的繁體中文(英文則像母語者隨手寫的),禁用 AI 常見的開場白、路標詞、空泛拔高、翻譯腔與簡報式排版,直到使用者說關閉。編輯模式:使用者說「去 AI 味」「說人話」「改自然」「不要像模板」「幫我審稿」,或要改寫貼文、文案、Email、文章、技術文件、小說時啟動,在不更動事實、數字、引用與作者立場的前提下清掉模板感。Also handles English requests to strip AI writing style…
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Build and execute multi-step prompt chains for complex tasks.