Reverse-engineer successful affiliate strategies from competitors. Use this skill when the user asks about spying on competitors, researching what other affiliates promote, analyzing competitor affiliate sites, understanding how top affiliates in a niche make money, or says "what programs does X promote", "how does [site] make money", "what affiliate strategy does this site use", "spy on competitor affiliates", "reverse engineer affiliate site", "copy what works in my niche", "who are the top affiliates in X niche", "what content gets traffic in my niche", "competitor affiliate analysis".
Instrucciones de origen · Vista previa de solo lectura
name
competitor-spy
description
Reverse-engineer successful affiliate strategies from competitors. Use this skill when the user asks about spying on competitors, researching what other affiliates promote, analyzing competitor affiliate sites, understanding how top affiliates in a niche make money, or says "what programs does X promote", "how does [site] make money", "what affiliate strategy does this site use", "spy on competitor affiliates", "reverse engineer affiliate site", "copy what works in my niche", "who are the top affiliates in X niche", "what content gets traffic in my niche", "competitor affiliate analysis".
Analyze competitor affiliate sites, YouTube channels, and social profiles to
surface which programs they promote, what content drives their traffic, and
which strategies are worth replicating. Outputs an actionable reverse-engineering
report so you can skip years of trial and error.
Stage
This skill belongs to Stage S1: Research
When to Use
User wants to know what programs are working in a specific niche
User has a competitor site/channel in mind and wants to understand their strategy
User is entering a new niche and wants a shortcut to what works
User wants to find underserved content gaps a competitor hasn't covered
User asks "how do top affiliates in [niche] make money?"
Input Schema
{
competitor_url: string # (optional) Direct URL to competitor site, channel, or profile
niche: string # (optional) Niche to analyze if no specific competitor given
platform: string # (optional) "blog" | "youtube" | "tiktok" | "twitter" | "newsletter"
depth: string # (optional, default: "standard") "quick" | "standard" | "deep"
focus: string # (optional) "programs" | "content" | "traffic" | "all"
}
Workflow
Step 1: Identify Competitors to Analyze
If competitor_url is provided, skip to Step 2.
If only niche is provided, find 3-5 top competitors:
web_search "best [niche] affiliate sites" — look for review/comparison sites
web_search "[niche] review site affiliate" — find review-first monetization models
web_search "[niche] blog affiliate income report" — income reports reveal programs
Look at their top content: "Best X", "X vs Y", "X Review", "X Alternatives"
Every product featured prominently = likely affiliate relationship
Products mentioned with a CTA button ("Try X Free", "Get X") = strong affiliate signal
Method C — Disclosure scan:
Search page for "affiliate", "commission", "sponsored", "partner" disclosures
These legally required disclosures often appear at top/bottom and reveal programs
Method D — Income reports (if available):
web_search "[site name] income report affiliate" — some affiliates publish earnings
web_search "[creator name] how I make money affiliate" — creator transparency posts
Extract for each program found: name, estimated prominence (primary/secondary/mentioned),
content type promoting it, and whether it appears on openaffiliate.dev.
Identify which content format gets them the highest engagement
Compare their engagement against trending-content-scout benchmark (if available)
Without API (default):
web_search "[competitor name] youtube channel" → find their channel
web_fetch channel page → extract view counts from visible videos
web_search "[competitor name] tiktok" → find top videos with view counts
web_search "[competitor name] best video" → find their highest-performing content
Note: approximate data, but reveals relative performance patterns
Extract for each competitor:
Avg engagement score — how well does their content perform overall?
Strongest platform — where do they get the most traction?
Weakest platform — which platforms are they ignoring? (gap to exploit)
Top performing content — their 3-5 best pieces by engagement
Format that works for them — which content format gets them the most engagement?
Add these to the competitor assessment table in Step 5:
Dimension
Score (1-10)
Assessment
Content Engagement
—
How well does their content perform? High = proven demand, low = weak execution
Platform Strength
—
Which platform are they strongest on? Which are they ignoring?
Step 3: Analyze Their Content Strategy
For each competitor, extract:
Content patterns:
Most common formats: listicles ("10 best X"), comparisons ("X vs Y"), tutorials,
reviews, roundups, case studies
Average content depth: shallow (<1000 words), standard (1000-3000), deep (3000+)
Publishing frequency: estimate from visible dates or web_search "site:[domain] 2024"
Content freshness: are articles updated? When?
Traffic indicators (from web search signals):
web_search "site:[domain]" — rough page count
Search for their brand name — how much branded traffic/discussion?
Look for "X review" queries in their content — review content = high buyer intent
SEO and social signals:
Do they rank for "[product] review" terms? (indicates SEO strategy)
Active social profiles linked from site? Which platforms?
Do they have a newsletter/email list? (footer signup forms)
Step 4: Find Content Gaps
Compare competitor content to what's NOT covered:
Products they promote but haven't done deep comparison posts for
Common user questions (from YouTube comments, Reddit threads, forums) they haven't answered
New product launches in the niche that competitors haven't covered yet
Angles competitors avoid (negative reviews, honest cons, "X is not for everyone")
Use web_search "reddit [niche] [product] problems" to find pain points no affiliate
has addressed honestly — these make high-converting, low-competition content.
Step 5: Score Competitor Strategies
For each competitor, assess:
Dimension
Score (1-10)
Assessment
Program Quality
—
Are they promoting high-commission recurring programs or low-margin one-off?
Content Quality
—
Shallow listicles vs. deep genuine reviews
SEO Sophistication
—
Thin content vs. well-structured, keyword-targeted
Monetization Diversity
—
One program vs. multiple revenue streams
Replicability
—
How hard is it to do what they do, but better?
Higher replicability score = easier to beat them.
Step 6: Build the Intelligence Report
Synthesize findings into a 3-part report:
Programs worth stealing — top programs their strategy validates
Content formats that clearly work — patterns worth replicating
Gaps to exploit — angles they've missed that you can own
Step 7: Self-Validation
Before presenting output, verify:
Confidence levels match evidence strength (confirmed = affiliate link found, likely = brand mention pattern, possible = inferred)
Programs cross-checked on openaffiliate.dev where possible
Replicability score accounts for barriers (domain authority, team size)
No hallucinated competitor data — all claims traceable to web_search results
If any check fails, fix the output before delivering. Do not flag the checklist to the user — just ensure the output passes.
Output Schema
{
output_schema_version: "1.0.0" # Semver — bump major on breaking changes
competitors_analyzed: [
{
url: string # Competitor URL
niche: string # Their niche focus
estimated_programs: string[] # Programs they appear to promote
top_content_formats: string[] # ["listicle", "comparison", "tutorial"]
estimated_traffic: string # "low" | "medium" | "high" (inferred from signals)
replicability_score: number # 1-10
avg_engagement_score: number # Average engagement across their content
strongest_platform: string # Platform where they perform best
weakest_platform: string # Platform they're ignoring — gap to exploit
top_performing_content: string[] # Their 3-5 best pieces by engagement
}
]
validated_programs: [
{
name: string # "ConvertKit"
promoted_by: string[] # Which competitors promote it
confidence: string # "confirmed" | "likely" | "possible"
openaffiliate_url: string | null # If found on openaffiliate.dev
}
]
content_gaps: string[] # Opportunities to fill
recommended_programs: string[] # Top programs to prioritize based on analysis
recommended_next_skill: string # "affiliate-program-search"
}
Output Format
## Competitor Intelligence Report: [Niche]
### Competitors Analyzed
| Competitor | Programs Found | Content Focus | Replicability |
|-----------|---------------|---------------|---------------|
| [site1.com] | [Program A, B, C] | Best-of lists, comparisons | 7/10 |
| [site2.com] | [Program D, E] | YouTube reviews | 8/10 |
---
### Programs Worth Promoting (Validated by Competitors)
| Program | Promoted By | Evidence | On openaffiliate.dev |
|---------|------------|----------|---------------------|
| [Program A] | [2 competitors] | Prominent CTA buttons, review posts | Yes |
| [Program B] | [1 competitor] | Income report mention | Check manually |
---
### Content Formats That Work in This Niche
1. **[Format 1]:** [What it is, why it works, example from competitor]
2. **[Format 2]:** [...]
3. **[Format 3]:** [...]
---
### Content Gaps You Can Exploit
1. **[Gap 1]:** [What's missing, why it's valuable, how to fill it]
2. **[Gap 2]:** [...]
3. **[Gap 3]:** [...]
---
## Next Steps
1. Run `affiliate-program-search` to evaluate the top validated programs
2. Run `commission-calculator` to compare earnings potential across programs
3. Start with the highest-gap content angle: [Gap 1] for [Program A]
Error Handling
Competitor URL blocked or paywalled: Fall back to web_search signals (Google cache,
SimilarWeb mentions, blog posts about the competitor). Note limitations in report.
No obvious affiliate links found: Competitor may use native ads or direct sponsorships
instead. Flag this and look for brand mention patterns.
Niche too broad: Ask user to narrow to a sub-niche or pick one platform to focus analysis on.
No competitors found: Niche may be too new or too narrow. Broaden one step and re-search.
If still empty, this itself is a signal — could be a gap opportunity.
Competitor is a large media company (Forbes, Wirecutter): Scale down — these aren't
replicable. Find indie affiliate sites instead (web_search "[niche] best [product] blog").
Examples
Example 1:
User: "Spy on what affiliate programs income school recommends"
→ web_fetch incomeschool.com, look for affiliate disclosures and outbound links
→ Find: Bluehost, Ezoic, Rank Math, Jasper — extract with confidence levels
→ Map to openaffiliate.dev programs
→ Output intelligence report with content gaps in their niche
Example 2:
User: "What affiliate strategy do top YouTubers use in the AI tools niche?"
→ Find 3-5 AI tools YouTubers via web_search
→ Analyze video descriptions for affiliate links (common pattern: "links below")
→ Extract: most promote 5-10 tools consistently, heavy on comparison content
→ Identify gap: no one doing "best AI tools for [specific job role]" content
Example 3:
User: "I'm entering the email marketing niche, help me spy on competitors"
→ Find competitors: emailtooltester.com, emailvendorselection.com, etc.
→ Extract programs: ConvertKit, ActiveCampaign, GetResponse, Brevo
→ Content gap: all sites focus on features, none do "email marketing ROI by industry"
→ Recommend: start with ConvertKit (recurring, high commission), fill the ROI gap
References
affiliate-program-search/references/openaffiliate-api.md — validate found programs on openaffiliate.dev
shared/references/affiliate-glossary.md — affiliate link pattern reference
