v1.0.0 to v1.0.1

- 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".

- 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"

- version: "1.0"

- Help affiliate marketers research, evaluate, and pick winning programs to promote.

- Data source: [openaffiliate.dev](https://openaffiliate.dev/?utm_source=affiliate-skills) — 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>&utm_source=affiliate-skills` — 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: Score Programs

-

- Apply the scoring framework from `references/scoring-criteria.md`.

-

- Score each program on 5 dimensions (1-10 scale):

- 1. **Earning Potential** (30%) — commission %, recurring vs one-time, product price

- 2. **Content Potential** (25%) — visual demo, free tier, content angles

- 3. **Market Demand** (20%) — search volume, trend direction, market size

- 4. **Competition Level** (15%) — fewer affiliates promoting = higher score

- 5. **Trust Factor** (10%) — product quality, reputation, stars on openaffiliate.dev

-

- Overall = weighted average. Verdict: 7.5+ "Strong Pick" / 5.5-7.4 "Worth Testing" / <5.5 "Skip".

-

- For dimensions that require external data (Market Demand, Competition Level), use `web_search` to check Google results count for "[product] review" and "[product] affiliate" queries.

-

- ### Step 4: Present Recommendation

-

- ### Step 5: Self-Validation

-

- Before presenting output, verify:

-

- - [ ] All scored programs have `reward_value` from API data, not hallucinated

- - [ ] `cookie_days` is numeric and from API response

- - [ ] Top Pick verdict matches score threshold (≥7.5 = Strong Pick, ≥6 = Worth Considering)

- - [ ] Market Demand and Competition scores cite the search query used

- - [ ] Stale data (>6 months) is flagged with warning

-

- If any check fails, fix the output before delivering. Do not flag the checklist to the user — just ensure the output passes.

-

- ## Output Schema

-

- Other skills (viral-post-writer, affiliate-blog-builder, etc.) consume these fields from conversation context:

-

- ```

- {

- output_schema_version: "1.0.0" # Semver — bump major on breaking changes

- recommended_program: {

- name: string # "HeyGen"

- slug: string # "heygen"

- reward_value: string # "30%"

- reward_type: string # "cps_recurring"

- reward_duration: string # "12 months"

- cookie_days: number # 60

- description: string # Short product description

- tags: string[] # ["ai", "video"]

- url: string # Product website

- }

- score: {

- overall: number # 8.2

- verdict: string # "Strong Pick"

- reasoning: string # Why this is the top pick

- }

- runner_up: Program | null # Same structure, second choice

- all_scored: ProgramScore[] # Full list of scored programs

- }

- ```

-

- ## Output Format

-

- ```

- ## Programs Found

-

- | Program | Commission | Type | Cookie | Stars | Score |

- |---------|-----------|------|--------|-------|-------|

- | HeyGen | 30% | Recurring | 60d | ⭐ 42 | 8.2/10 |

- | ... | ... | ... | ... | ... | .../10 |

-

- ## Top Pick: [Program Name]

-

- **Why:** [2-3 sentences explaining why this is the best fit]

-

- | Dimension | Score | Note |

- |-----------|-------|------|

- | Earning Potential | 8/10 | 30% recurring on $24-48/mo |

- | Content Potential | 9/10 | Visual AI video, easy to demo |

- | Market Demand | 8/10 | AI video trending, high search volume |

- | Competition | 6/10 | Growing number of affiliates |

- | Trust Factor | 8/10 | Strong brand, 42 stars on openaffiliate.dev |

- | **Overall** | **8.2/10** | **Strong Pick** |

-

- ## Runner-up: [Program Name]

-

- **Why:** [1-2 sentences]

-

- ## Next Steps

-

- 1. Sign up for [Program] affiliate program → [search for signup page]

- 2. Run `viral-post-writer` to create content for this product

- 3. Run `affiliate-blog-builder` to write a review post

- ```

-

- ## Error Handling

-

- - **API unavailable:** Fall back to web_fetch method (see `references/openaffiliate-api.md` Method 2)

- - **No programs match criteria:** Broaden search (remove strictest filter first), explain to user what was relaxed

- - **Stale data (program updated_at > 6 months):** Flag with "Data may be outdated, verify on product website"

- - **User gives no criteria:** Use defaults (AI/SaaS, recurring, 20%+, content creator audience)

- - **Program not on openaffiliate.dev:** Use `web_search` to find program details directly, still apply scoring framework

-

- ## Examples

-

- **Example 1:**

- User: "I want to promote AI video tools, commission recurring, at least 20%"

- → Search openaffiliate.dev for programs tagged "ai" or "video": `GET /api/programs?q=ai+video`

- → Filter: reward_type = cps_recurring, reward_value ≥ 20%

- → Score and rank: HeyGen, Synthesia, ElevenLabs, InVideo AI...

- → Recommend top pick with full scorecard

-

- **Example 2:**

- User: "Compare HeyGen vs Synthesia for my LinkedIn audience"

- → Fetch both from openaffiliate.dev: `GET /api/programs/heygen` and `GET /api/programs/synthesia`

- → Score both, emphasize Content Potential for LinkedIn

- → Side-by-side comparison table + recommendation

- → Note: LinkedIn audience = B2B, weight higher-price products

-

- **Example 3:**

- User: "I'm a beginner, what should I promote first?"

- → Default criteria: AI/SaaS, recurring, easy-to-demo products

- → Weight beginner-friendly factors: free tier, low payout threshold, strong brand

- → Recommend program with easiest path to first commission

-

- ## References

-

- - `references/scoring-criteria.md` — the 5-dimension scoring framework with rubrics

- - `references/openaffiliate-api.md` — how to fetch data from openaffiliate.dev (API + fallback)

- - `references/platform-rules.md` — platform-specific considerations when recommending programs

- - `shared/references/flywheel-connections.md` — master flywheel connection map

-

- ## Flywheel Connections

-

- ### Feeds Into

- - `viral-post-writer` (S2) — `recommended_program` product data for social content

- - `twitter-thread-writer` (S2) — `recommended_program` for Twitter threads

- - `reddit-post-writer` (S2) — `recommended_program` for Reddit posts

- - `content-pillar-atomizer` (S2) — `recommended_program` for content creation

- - `affiliate-blog-builder` (S3) — `recommended_program` for blog articles

- - `landing-page-creator` (S4) — `recommended_program` for landing pages

- - `grand-slam-offer` (S4) — `recommended_program` for offer design

- - `bonus-stack-builder` (S4) — product data for bonus design

-

- ### Fed By

- - `conversion-tracker` (S6) — top converting niches → search for more programs in winning niches

- - `performance-report` (S6) — performance data showing which program types convert best

- ### Feedback Loop

- - Conversion data from S6 reveals which program characteristics (commission type, cookie length, niche) correlate with highest earnings → refine search criteria on next run

- ```yaml

- chain_metadata:

- skill_slug: "affiliate-program-search"

- stage: "research"

- timestamp: string

- suggested_next:

- - "purple-cow-audit"

- - "viral-post-writer"

- - "landing-page-creator"

- - "grand-slam-offer"

- ```