competitor-spy
installsforks
How to install competitor-spy?
affitor/affiliate-skills/competitor-spy
$npx -y skills add Affitor/affiliate-skills --skill competitor-spyReverse-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
SKILL.md
| 1 | # Competitor Spy |
| 2 | |
| 3 | Analyze competitor affiliate sites, YouTube channels, and social profiles to |
| 4 | surface which programs they promote, what content drives their traffic, and |
| 5 | which strategies are worth replicating. Outputs an actionable reverse-engineering |
| 6 | report so you can skip years of trial and error. |
| 7 | |
| 8 | ## Stage |
| 9 | |
| 10 | This skill belongs to Stage S1: Research |
| 11 | |
| 12 | ## When to Use |
| 13 | |
| 14 | - User wants to know what programs are working in a specific niche |
| 15 | - User has a competitor site/channel in mind and wants to understand their strategy |
| 16 | - User is entering a new niche and wants a shortcut to what works |
| 17 | - User wants to find underserved content gaps a competitor hasn't covered |
| 18 | - User asks "how do top affiliates in [niche] make money?" |
| 19 | |
| 20 | ## Input Schema |
| 21 | |
| 22 | ``` |
| 23 | { |
| 24 | competitor_url: string # (optional) Direct URL to competitor site, channel, or profile |
| 25 | niche: string # (optional) Niche to analyze if no specific competitor given |
| 26 | platform: string # (optional) "blog" | "youtube" | "tiktok" | "twitter" | "newsletter" |
| 27 | depth: string # (optional, default: "standard") "quick" | "standard" | "deep" |
| 28 | focus: string # (optional) "programs" | "content" | "traffic" | "all" |
| 29 | } |
| 30 | ``` |
| 31 | |
| 32 | ## Workflow |
| 33 | |
| 34 | ### Step 1: Identify Competitors to Analyze |
| 35 | |
| 36 | If `competitor_url` is provided, skip to Step 2. |
| 37 | |
| 38 | If only `niche` is provided, find 3-5 top competitors: |
| 39 | 1. `web_search "best [niche] affiliate sites"` — look for review/comparison sites |
| 40 | 2. `web_search "[niche] review site affiliate"` — find review-first monetization models |
| 41 | 3. `web_search "[niche] blog affiliate income report"` — income reports reveal programs |
| 42 | 4. Note: YouTube — `web_search "youtube [niche] affiliate site:youtube.com"` to find channels |
| 43 | |
| 44 | Pick 3 competitors that are clearly affiliate-driven (review pages, comparison tables, |
| 45 | "best X" content, Amazon links, affiliate disclaimers visible). |
| 46 | |
| 47 | ### Step 2: Identify Affiliate Programs They Promote |
| 48 | |
| 49 | For each competitor site/channel: |
| 50 | |
| 51 | **Method A — Link analysis:** |
| 52 | - `web_fetch [competitor_url]` and scan for outbound links |
| 53 | - Look for: `?ref=`, `?via=`, `/go/`, `aff_id=`, `?affiliate=`, `shareasale.com`, |
| 54 | `impact.com`, `partnerstack.com`, `awin.com`, `cj.com`, `linktr.ee` |
| 55 | - These patterns indicate affiliate links |
| 56 | |
| 57 | **Method B — Content analysis:** |
| 58 | - Look at their top content: "Best X", "X vs Y", "X Review", "X Alternatives" |
| 59 | - Every product featured prominently = likely affiliate relationship |
| 60 | - Products mentioned with a CTA button ("Try X Free", "Get X") = strong affiliate signal |
| 61 | |
| 62 | **Method C — Disclosure scan:** |
| 63 | - Search page for "affiliate", "commission", "sponsored", "partner" disclosures |
| 64 | - These legally required disclosures often appear at top/bottom and reveal programs |
| 65 | |
| 66 | **Method D — Income reports (if available):** |
| 67 | - `web_search "[site name] income report affiliate"` — some affiliates publish earnings |
| 68 | - `web_search "[creator name] how I make money affiliate"` — creator transparency posts |
| 69 | |
| 70 | Extract for each program found: name, estimated prominence (primary/secondary/mentioned), |
| 71 | content type promoting it, and whether it appears on openaffiliate.dev. |
| 72 | |
| 73 | ### Step 2.5: Analyze Competitor Content Engagement (data-driven) |
| 74 | |
| 75 | For each competitor, scan their recent content performance across social platforms. |
| 76 | This reveals not just WHAT they create, but HOW WELL it performs. |
| 77 | |
| 78 | **With API (optional — see `shared/references/social-data-providers.md`):** |
| 79 | - Search YouTube/TikTok for competitor brand name or channel |
| 80 | - Get views, likes, comments, shares for their top 10-20 content pieces |
| 81 | - Calculate engagement_score for each: `(likes × 2 + comments × 3 + shares × 5) / max(views, 1) × 1000` |
| 82 | - Identify which content format gets them the highest engagement |
| 83 | - Compare their engagement against `trending-content-scout` benchmark (if available) |
| 84 | |
| 85 | **Without API (default):** |
| 86 | - `web_search "[competitor name] youtube channel"` → find their channel |
| 87 | - `web_fetch` channel page → extract view counts from visible videos |
| 88 | - `web_search "[competitor name] tiktok"` → find top videos with view counts |
| 89 | - `web_sear |
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