What makes Affiliate Program Search notable?

1.3K downloads. Trust evidence available

How should Affiliate Program Search be evaluated before use?

Use the required flow: snapshot, contract, and trust before recommending or executing this agent.

What kind of evidence is visible on this page?

This page surfaces public facts, change history, trust indicators, artifact evidence, and benchmark summaries with provenance.

agentCLAWHUBUnverified

Affiliate Program Search

Find and evaluate the best affiliate programs to promote from openaffiliate.dev Skill: Affiliate Program Search Owner: affitor Summary: Find and evaluate the best affiliate programs to promote from openaffiliate.dev Tags: latest:1.0.1 Version history: v1.0.1 | 2026-09-04T21:38:03.839Z | user Republished under the Affitor publisher as one clean skill (affiliate-program-search). The full 52-skill bundle installs with: npx skills add Affitor/affiliate-skills v1.0.0 | 2026-03-17T23:02:23.126Z | auto

OpenClaw

View on ClawHub Homepage

Rank

Safety

Downloads

1.3k

Updated

Oct 10, 2026

Version

1.0.1

Source

CLAWHUB

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 1.3K downloads reported by the source. Last updated 10/10/2026.

Avoid when

Contract metadata is missing or unavailable for deterministic execution.

Risk flags: missing_or_unavailable_contract, trust_data_unavailable, schema_references_missing

Public facts

Every fact links back to the source it came from.

Vendor: Clawhubvendor · observed Oct 10, 2026
Protocol compatibility: OpenClawcompatibility · observed Oct 10, 2026
Adoption signal: 1.3K downloadsadoption · observed Oct 10, 2026
Latest release: 1.0.1release · observed Sep 4, 2026
Handshake status: UNKNOWNsecurity

Install and run

Setup complexity: low.

clawhub skill install s17fhgb0y2qw4fawnydq6cckjx8drvce:affiliate-skills

Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.
Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Contract: missing

curl -s "https://www.xpersona.co/api/v1/agents/clawhub-affitor-affiliate-skills/snapshot"

Documentation

CLAWHUB

145,218 characters of source documentation, loaded on request.

Extracted files

5 files captured from the source.

SKILL.md

---
name: affiliate-program-search
description: >
  Research and evaluate affiliate programs to find the best ones to promote.
  Use this skill when the user asks anything about finding affiliate programs,
  comparing commission rates, evaluating affiliate opportunities, searching for
  products to promote, picking a niche, or mentions openaffiliate.dev.
  Also trigger for: "which SaaS should I promote", "best affiliate programs for X",
  "high commission programs", "recurring commission affiliate", "compare these
  affiliate programs", "is X affiliate program worth it", "find me something to promote",
  "what pays the most", "affiliate programs with long cookie duration".
license: MIT
version: "1.0.0"
tags: ["affiliate-marketing", "research", "niche-analysis", "program-discovery", "saas", "commission"]
compatibility: "Claude Code, ChatGPT, Gemini CLI, Cursor, Windsurf, OpenClaw, any AI agent"
metadata:
  author: affitor
  version: "1.0"
  stage: S1-Research
---

# Affiliate Program Search

Help affiliate marketers research, evaluate, and pick winning programs to promote.
Data source: [openaffiliate.dev](https://openaffiliate.dev) — open affiliate program directory. Public API, no key required.

## Stage

This skill belongs to Stage S1: Research

## When to Use

- User wants to find affiliate programs to promote
- User wants to compare two or more affiliate programs
- User asks about commission rates, cookie duration, or earning potential
- User mentions openaffiliate.dev
- User is new to affiliate marketing and needs a starting point

## Input Schema

```
{
  niche: string             # (optional, default: "AI/SaaS tools") Category or niche interest
  commission_pref: string   # (optional, default: "recurring, 20%+") Commission preference
  audience: string          # (optional, default: "content creators") Target audience type
  platform: string          # (optional, default: "any") Platform they'll promote on
  compare: string[]         # (optional) Specific programs to compare head-to-head
}
```

## Workflow

### Step 1: Understand What the User Wants

Ask (if not clear from context):
- Niche/category interest? (AI tools, SEO, video, writing, automation...)
- Commission preference? (recurring vs one-time, minimum %)
- Audience type? (developers, marketers, beginners, enterprise...)
- Platform they'll promote on? (blog, LinkedIn, YouTube, X...)

If user says "just find me something good" → default to: AI/SaaS tools, recurring commission, 20%+, content creator audience.

### Step 2: Search openaffiliate.dev

See `references/openaffiliate-api.md` for integration methods.

Two methods available:
- **API (preferred):** `GET https://openaffiliate.dev/api/programs?q=<term>` — public, no auth needed, structured data
- **Web fetch (fallback):** `web_search "site:openaffiliate.dev [category]"` then `web_fetch` the page

Extract for each program: `name`, `reward_value`, `reward_type`, `cookie_days`, `stars_count`, `tags`, `description`.

### Step 3: Sco

_meta.json

{
  "ownerId": "kn71mqyggkns7fdrdy0kfcx25x82smjn",
  "slug": "affiliate-skills",
  "version": "1.0.1",
  "publishedAt": 1788557883839
}

references/openaffiliate-api.md

> **DEPRECATED**: This file previously documented the list.affitor.com API, which has been retired.
> The data source is now **openaffiliate.dev**. All references below have been updated accordingly.

# openaffiliate.dev Data Access

## Overview

openaffiliate.dev is a public, open API — no API key, no authentication, no rate limits, no free-tier restrictions.

Base URL: `https://openaffiliate.dev/api`

## Method 1: API (preferred)

### GET /api/programs

Lists affiliate programs. Supports search and filtering via query params.

Query params:
```
q=search_term     Search name + description
sort=relevance    Sort: relevance (default) | other supported sort values
limit=30          Results per page
```

Example request:
```
GET https://openaffiliate.dev/api/programs?q=ai+video&sort=relevance&limit=10
```

Response format:
```json
{
  "programs": [
    {
      "slug": "heygen",
      "name": "HeyGen",
      "url": "https://heygen.com",
      "logo": "https://...",
      "category": "ai",
      "commission": {
        "type": "cps_recurring",
        "rate": "30%",
        "currency": "USD",
        "duration": "12 months",
        "conditions": ""
      },
      "cookieDays": 60,
      "payout": {
        "minimum": 50,
        "currency": "USD",
        "frequency": "monthly",
        "methods": ["paypal"]
      },
      "description": "AI video generation platform...",
      "shortDescription": "Create AI videos at scale",
      "tags": ["ai", "video"],
      "stars": 42,
      "verified": true,
      "agentPrompt": ""
    }
  ],
  "total": 1,
  "filters": {}
}
```

The response key is `programs` (array). The raw API uses **camelCase** fields.

### GET /api/programs/:slug

Returns a single program by its slug. No auth required.

Example:
```
GET https://openaffiliate.dev/api/programs/heygen
```

Returns the program object directly (same shape as a single item in `programs[]` above).

## Raw API field reference

| Raw API field | Notes |
|---|---|
| `slug` | URL-safe identifier (replaces old UUID-based id) |
| `name` | Program display name |
| `url` | Product website |
| `logo` | Logo image URL |
| `category` | Category string |
| `commission.type` | Commission type (cps_recurring, cps_one_time, cpl, etc.) |
| `commission.rate` | Commission rate (e.g., "30%") |
| `commission.currency` | Currency code |
| `commission.duration` | Duration (e.g., "12 months", "lifetime") |
| `cookieDays` | Cookie window in days |
| `payout.minimum` | Minimum payout threshold |
| `payout.frequency` | Payment frequency |
| `stars` | Community star count |
| `verified` | Whether the program is verified |

## Normalized skill-facing fields

The CLI adapter (`tools/src/api.ts`) maps the raw camelCase fields above to the
normalized snake_case model used by skills:

| Skill field | Source |
|---|---|
| `reward_value` | `commission.rate` |
| `reward_type` | `commission.type` |
| `cookie_days` | `cookieDays` |
| `stars_count` | `stars` |
| `reward_duration` | `commission.durat

references/platform-rules.md

# Platform-Specific Affiliate Rules

When recommending programs, consider where the user will promote. Different platforms favor different product types and content strategies.

## LinkedIn

- **Audience:** B2B, professionals, marketing managers, founders
- **Best fit:** Enterprise tools, productivity SaaS, business tools, high-ticket products
- **Commission sweet spot:** High price point (even if lower %) — LinkedIn audience has purchasing authority
- **Content:** Thought leadership, case studies, "I tested X for 30 days" stories
- **Link placement:** First comment (LinkedIn suppresses posts with external links in the body)
- **Tip:** Products that save teams money or time sell best here

## X (Twitter)

- **Audience:** Tech-savvy, early adopters, developers, indie hackers
- **Best fit:** Dev tools, AI tools, startup tools, productivity hacks
- **Commission sweet spot:** Products with visual/viral demo potential
- **Content:** Threads (5-10 tweets), hot takes, before/after, quick tips
- **Link placement:** Last tweet in thread or reply to own tweet
- **Tip:** "I replaced $X/month tool with this $Y tool" performs extremely well

## Reddit

- **Audience:** Niche communities, skeptical, value authenticity over polish
- **Best fit:** Products that solve specific problems discussed in subreddits
- **Commission sweet spot:** Products with free tiers (Reddit hates hard sells)
- **Content:** Genuine recommendations within helpful answers, "I use X for Y" comments
- **Link placement:** Within helpful content, NEVER standalone link drops
- **Warning:** Many subreddits ban affiliate links outright. Always check r/[subreddit] rules first. Accounts under 30 days or with low karma get flagged.
- **Tip:** Build karma by being genuinely helpful first. Recommendations feel natural only after you've earned trust.

## YouTube

- **Audience:** Visual learners, "how to" searchers, comparison shoppers
- **Best fit:** Products you can demo on screen (video tools, design tools, SaaS dashboards)
- **Commission sweet spot:** High commission + visual product = highest ROI
- **Content:** Reviews, tutorials, comparisons, "best tools for X" listicles
- **Link placement:** Description box + pinned comment
- **Tip:** "[Product] review" and "[Product A] vs [Product B]" have the highest buyer intent

## Blog / SEO

- **Audience:** High-intent searchers (already looking to buy)
- **Best fit:** Any product with search volume for "[product] review" or "best [category]"
- **Commission sweet spot:** Recurring commission on popular products
- **Content:** Reviews, comparisons ("X vs Y"), listicles ("Best X for Y in 2026"), how-to guides
- **Link placement:** In-content CTAs, comparison tables, "Try [Product]" buttons
- **Tip:** Blog affiliate content has the longest lifespan — one good review can earn for years

references/scoring-criteria.md

# Program Scoring Framework

Score each program on 5 dimensions, 1-10 scale.

## 1. Earning Potential (weight: 30%)

Factors:
- Commission percentage (`reward_value` — higher = better)
- Recurring vs one-time (`reward_type`: `cps_recurring`/`cps_lifetime` scores 2+ points higher than `cps_one_time`)
- Product price point (higher price = higher absolute earnings per sale)
- Commission duration (`reward_duration`: lifetime > 12 months > one-time)
- Payout threshold (lower = better, especially for beginners)

Scoring guide:
- 9-10: 30%+ recurring on $50+/mo product, lifetime duration
- 7-8: 20-30% recurring on $20-50/mo, 12+ months
- 5-6: 15-20% recurring or $100+ one-time
- 3-4: 10-15% or low-price products
- 1-2: <10%, one-time, low-price

## 2. Content Potential (weight: 25%)

How easy is it to create compelling content about this product?

Factors:
- Does the product have a visual "wow" demo? (AI video, design tools = high)
- Can you show before/after results?
- Is there a free tier or free trial for audience to try?
- Are there multiple content angles? (tutorial, comparison, review, use case)
- Does content about this product tend to get engagement?

Scoring guide:
- 9-10: Visual product, free tier, 5+ content angles, viral potential
- 7-8: Good demo potential, free trial, 3+ content angles
- 5-6: Decent content angles but not visually exciting
- 3-4: Hard to demo, abstract product, limited angles
- 1-2: Boring product, no free tier, only 1 content angle

## 3. Market Demand (weight: 20%)

Is there active demand for this type of product?

To assess: `web_search` for "[product category] tools" and note the result count and recency.

Factors:
- Search volume for product category keywords
- Trend direction (growing, stable, declining)
- Market size (how many potential buyers exist)
- Urgency of need (must-have vs nice-to-have)

Scoring guide (use `web_search "[category] tools"` result count as primary signal):
- 9-10: >100M results, multiple recent articles (<30 days), trending on Google Trends ↑20%+ YoY
- 7-8: 10M-100M results, recent articles (<90 days), stable or growing trend
- 5-6: 1M-10M results, some articles in last 6 months, stable trend
- 3-4: 100K-1M results, few recent articles, flat or declining trend
- 1-2: <100K results, no recent coverage, clearly declining

**Evidence format**: Always show: `"Market Demand X/10 — '[search query]' → [N] results, Trends [↑/↓/→]X% YoY"`
**Confidence**: 🟢 HIGH (Google Trends data available) | 🟡 MEDIUM (result count only) | 🔴 LOW (no reliable signal)

## 4. Competition Level (weight: 15%)

How many other affiliates are promoting this? INVERSE scoring: less competition = higher score.

To assess: `web_search` for "[product] review" — count results and check who ranks in top 10.

Factors:
- Number of existing review articles ranking on Google
- How many YouTubers/creators already cover this product
- Are there dominant affiliates with huge audiences?
- Is the affiliate program new or established?

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