agentmods.dev

cursorrules

A collection of 45 instruction-based workflows for affiliate marketing, covering research, content, SEO, outreach and analytics. They use live information from the Affitor API, a service that provides affiliate-program data.

In plain words
What is it for?
Use it to research affiliate programs, create marketing content, plan SEO and outreach, build landing pages, distribute campaigns and review results.
Why use it?
It gives an AI coding agent defined steps, inputs and outputs for recurring affiliate-marketing work. The workflows can be connected so one task’s result feeds the next.

Cursor rule for Cursor

639 2mo ago A scan 654 tokens original MIT
View the source file Affitor/affiliate-skills
Install

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.

agentmods
npx agentmods add rules/affitor/affiliate-skills/cursorrules
Clone the repo
git clone --depth 1 https://github.com/Affitor/affiliate-skills

Made for: Cursor.

Per session 654 This file is loaded in full into every session.
When invoked 654 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00654 $0.00654
Opus 5 $0.00327 $0.00327
Sonnet 5 $0.00131 $0.00131
Haiku 4.5 $0.00065 $0.00065

Measured 2d ago against content hash 598ae25ba742, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

cursorrules 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 2d 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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

.cursorrules · 54 lines

How it starts

The opening of the file, as written. The whole thing — 54 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Affitor Affiliate Skills — Cursor Rules

What This Repo Is

45 AI-powered skills for affiliate marketers. Each skill automates a specific workflow (content creation, program research, SEO, outreach, analytics, etc.) using live data from the Affitor API.

How Skills Work

  • Each skill lives in skills/<stage>/<skill-name>/SKILL.md
  • SKILL.md is a self-contained instruction file: it defines inputs, workflow steps, and expected outputs
  • Skills are designed to be chained — the output of one skill feeds the next
  • Run a skill by reading its SKILL.md and executing the documented workflow

Directory Layout

skills/          # Skills grouped by stage (research, content, blog, landing, distribution, analytics, automation, meta)
registry.json    # Master index of all 45 skills with metadata
API.md           # Full Affitor API reference
prompts/         # Bootstrap prompt for any AI
shared/
  references/    # Cross-skill reference docs (FTC rules, glossary, branding)

Affitor API

  • Base URL: https://openaffiliate.dev/api
  • Programs endpoint: GET /programs?q=<text>&sort=<relevance|trending|new|top>&limit=<n>
  • Single program: GET /programs/<slug>
  • Public, no API key or auth required
  • Raw API fields (camelCase, nested): slug, name, url, logo, category, commission.type, commission.rate, commission.duration, cookieDays, payout.*, description, shortDescription, tags[], stars, verified
  • CLI-normalized skill-facing fields (used in skill outputs):
    • reward_value — from commission.rate
    • reward_type — from commission.type
    • cookie_days — from cookieDays
    • stars_count — from stars
  • Always fetch real data from the API. Never fabricate program details.

Key Rules

  1. FTC disclosure required — any content that promotes an affiliate program must include a clear disclosure ("I may earn a commission..."). See shared/references/ftc-compliance.md.
  2. Data from API, not guesses — commission rates, cookie windows, and program names must come from live API responses.
  3. Portable output — skill outputs must work standalone (markdown, plain text, CSV). No platform-specific formatting unless the skill explicitly targets one.
  4. Follow the SKILL.md workflow exactly — each step is intentional. Don't skip steps.
  5. Chain outputs — skills are composable. Pass structured output from one skill as input to the next when building multi-step workflows.

Read the full file on GitHub · 54 lines

Changes

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.

  1. 2d ago First seen · 54 lines · 654 tokens per session scan A 598ae25ba742

Subscribe to this mod's changes

cursorrules is a cursor rule published in the GitHub repository Affitor/affiliate-skills (639 stars, last pushed 2mo ago), licensed MIT. It adds 654 tokens to every session, about $0.0033 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.

Analytics and metricsBackend and APIsCode reviewLLMaffiliate-marketingagent-skillsai-agentsclaudeclaude-code
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