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 Affitor/affiliate-skills --skill content-angle-rankergit 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/content-angle-ranker)<a href="https://agentmods.dev/skills/affitor/affiliate-skills/content-angle-ranker"><img src="https://agentmods.dev/badge/skills/affitor/affiliate-skills/content-angle-ranker/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/affitor/affiliate-skills/content-angle-ranker"><img src="https://agentmods.dev/badge/skills/affitor/affiliate-skills/content-angle-ranker.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00175 | $0.04986 |
| Opus 5 | $0.00088 | $0.02493 |
| Sonnet 5 | $0.00035 | $0.00997 |
| Haiku 4.5 | $0.00017 | $0.00499 |
Grade A, and why
content-angle-ranker 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- content-angle-ranker — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 456 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Content Angle Ranker
You have a keyword. You know the niche. But what specific content should you create? Which angle, format, and hook will actually perform? This skill answers that question with data — not gut feeling.
It takes engagement data (from trending-content-scout or live research) and ranks
8-12 content angle candidates by a weighted score combining platform fit, competition
level, engagement prediction, and creator fit. The output is a prioritized list with
a clear recommendation and direct handoff to content creation skills.
Think of it as /plan-ceo-review from gstack, but for content strategy: "What is
the 10-star version of this content?" — except the answer is backed by engagement data.
Stage
This skill belongs to Stage S1: Research — but it bridges directly into S2: Content Creation.
When to Use
- After
trending-content-scoutran — use its data to pick the best angle - User has a product/keyword but doesn't know what content to create
- User has multiple content ideas and wants to prioritize by data
- User wants to know: "If I only have time for ONE piece of content, what should it be?"
- Before running any S2 content skill (viral-post-writer, tiktok-script-writer, etc.)
Input Schema
keyword: string # (required if no scout_data) "AI video tools"
product: object # (optional) Affiliate product being promoted
name: string # "HeyGen"
description: string # What it does
url: string # Product URL or affiliate link
reward_value: string # Commission info — never shown in content
platform: string # (required) Target platform for content creation
# "youtube" | "tiktok" | "linkedin" | "x" | "reddit" | "blog"
creator_strengths: string[] # (optional) What the user is good at
# "storytelling" | "technical" | "humor" | "authority" |
# "visual" | "data" | "personal_experience"
audience: string # (optional) Target audience — "beginners", "developers", "small business owners"
time_budget: string # (optional) "30min" | "2hours" | "1day" — affects difficulty filter
custom_angles: string[] # (optional) User's own angle ideas to include in ranking
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 · 456 lines · 175 tokens per session scan A c036e50672c3
content-angle-ranker is a skill published in the GitHub repository Affitor/affiliate-skills (654 stars, last pushed 4d ago), licensed MIT. It adds 175 tokens to every session and 4,986 once invoked, about $0.0009 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.
Other skills, from other repositories
content-angle-ranker
Rank content angles by engagement data, competition level, and platform fit. Data-driven angle selection instead of guesswork. Use this skill when the user has a keyword or product and needs to decide WHAT to create, which angle to take, which format to use, or which platform to target. Triggers on: "what angle should…
content-pillar-atomizer
Take 1 blog post or article and generate 15-30 platform-native micro-content pieces. Not reformatting — re-contextualizing for each platform's culture. Triggers on: "atomize this content", "repurpose my blog post", "turn this into social posts", "content atomizer", "pillar content", "one to many content", "repurpose…
brainstorm
Multi-persona Round-Table mit domain-aware Personas (LLM wählt 4–6 themenspezifische Rollen); iterative Cross-Pollination bis TF-IDF-Konvergenz; Synthesizer ranked Top-N mit Pro/Contra.
twitter-thread-writer
Write X/Twitter threads that get bookmarked, shared, and drive affiliate clicks. Use this skill when the user asks about writing Twitter threads, X threads, tweet threads for affiliate marketing, or says "write a thread about X", "Twitter thread promoting X", "X thread for affiliate", "write tweets that go viral"…
content-research-brief
Research trending topics, collect source articles, and generate a structured research brief for content creation. Stop writing from thin air — write from real sources. Use this skill when the user wants to research a topic before writing, collect sources for an article, create a research-backed content brief, or says…
infographic-generator
Generate branded infographic specifications from any content or data. Outputs structured layout, copy, data visualization, and color scheme — ready to render as HTML/CSS, Satori, Canva, or any design tool. Use this skill when the user wants an infographic, data visual, social media image, comparison chart, stat card…