skill-finder

name	skill-finder
description	Find the right Affitor skill for your goal. Triggers on: "which skill should I use", "find me a skill", "what skills are available", "help me choose a skill", "skill for SEO", "skill for email", "explore skills", "I'm new to Affitor", "what can Affitor do", "search skills", "skill for blog writing", "skill for landing pages", "skill for analytics".
license	MIT
version	1.0.0
tags	["affiliate-marketing","meta","planning","compliance","discovery","skill-search"]
compatibility	Claude Code, ChatGPT, Gemini CLI, Cursor, Windsurf, OpenClaw, any AI agent
metadata	{"author":"affitor","version":"1.0","stage":"S8-Meta"}

Skill Finder

Search and discover Affitor skills by task, stage, keyword, or natural language goal. Returns a ranked list of matching skills with descriptions, input requirements, and recommended next steps. Output is a concise Markdown guide.

Stage

S8: Meta — The entry point to the entire Affitor ecosystem. New users don't know what's available. Experienced users forget skill names. Skill Finder bridges the gap — it reads the registry, matches intent to capability, and recommends the fastest path to the user's goal.

When to Use

• User is new to Affitor and asks "what can I do?" or "where do I start?"
• User describes a goal but doesn't name a specific skill
• User wants to find skills by stage (e.g., "what analytics skills exist?")
• User asks "which skill helps with [topic]?"
• User says anything like "find skill", "search skill", "explore skills"
• Chaining: recommended as the first skill for new users before S1-S7

Input Schema

query: string                  # REQUIRED — natural language: "I want to write a blog review"
                               # or "what skills help with SEO?" or "analytics skills"
stage_filter: string           # OPTIONAL — filter by stage: research | content | blog | landing
                               # | distribution | analytics | automation | meta
goal: string                   # OPTIONAL — broader goal: "first commission" | "scale to 1k"
                               # | "optimize conversions" | "automate my workflow"

Workflow

Step 1: Load Skill Catalog

Read registry.json from the repository root (or from conversation context if already loaded). Parse all skills with their stage, name, slug, and description.

Step 2: Match Query to Skills

Match the user's query against:

1. Skill names and slugs (exact match → top priority)
2. Skill descriptions (keyword overlap)
3. Stage labels and descriptions (if user is browsing by stage)
4. Inferred intent (e.g., "SEO" → seo-audit, affiliate-blog-builder)

If stage_filter is provided, restrict results to that stage.

Step 3: Rank Results

Rank matches by relevance:

1. Direct name/slug match
2. Description keyword match count
3. Stage alignment with user's apparent funnel position

Step 4: Recommend a Path

If the user's goal spans multiple stages, suggest a skill sequence:

• "You want to go from zero to first commission → S1 → S2 → S3 → S5"
• "You want to optimize existing content → S6 (seo-audit, ab-test-generator)"

Step 5: Output Results

Present top 3-5 matching skills with:

• Skill name and stage
• What it does (one sentence)
• What input it needs
• Example invocation prompt

Step 6: Self-Validation

Before presenting output, verify:

• All matched skills exist in the current registry
• Example prompts are copy-paste ready and grammatically correct
• Recommended path follows logical funnel sequence
• Relevance ranking: exact match > partial match > related
• Input needed descriptions match actual skill Input Schemas

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
matches:
  - skill: string              # skill slug
    stage: string              # e.g., "S6: Analytics"
    description: string        # one-sentence summary
    input_needed: string       # what the user needs to provide
    example_prompt: string     # copy-paste prompt to invoke the skill
    relevance: string          # "exact" | "high" | "related"

recommended_path:
  description: string          # why this path
  steps:
    - order: number
      skill: string
      action: string           # what this step accomplishes

Output Format

1. Matching Skills — table with skill name, stage, description, and relevance
2. How to Use — for each top match, show the exact prompt to invoke it
3. Recommended Path — if the goal spans multiple stages, a numbered sequence

Error Handling

• Empty query: "What are you trying to accomplish? For example: 'write a blog review', 'track conversions', or 'plan a full funnel'."
• No matches found: "No skills match '[query]'. Here are all available stages: [list stages]. Try describing your goal differently."
• Too broad query ("everything"): Show one skill per stage as a sampler, then ask: "Which stage interests you most?"

Examples

Example 1: Specific task query

User: "I want to write a blog review of an AI tool" Action: Match → affiliate-blog-builder (S3, exact), comparison-post-writer (S3, related), viral-post-writer (S2, related). Show top 3 with example prompts. Recommend: "Start with S1 affiliate-program-search to find the best program, then use S3 affiliate-blog-builder for the review."

Example 2: Stage browsing

User: "What analytics skills are available?" Action: Filter by analytics stage → show all 4: conversion-tracker, ab-test-generator, performance-report, seo-audit. Describe each with input requirements.

Example 3: Goal-oriented

User: "I'm new to affiliate marketing, where do I start?" Action: Recommend the beginner path: S1 (affiliate-program-search) → S2 (viral-post-writer) → S3 (affiliate-blog-builder) → S5 (bio-link-deployer). Explain each step in one sentence.

References

• registry.json — Machine-readable skill catalog. Read in Step 1.
• shared/references/flywheel-connections.md — master flywheel connection map

Flywheel Connections

Feeds Into

• Any skill — matched_skill routes the user to the right skill

Fed By

• registry.json — skill catalog with all 44 skills across 8 stages

Feedback Loop

• Track which skills are most frequently requested → surface popular skills higher in recommendations

chain_metadata:
  skill_slug: "skill-finder"
  stage: "meta"
  timestamp: string
  suggested_next: []  # Dynamic — depends on matched skill