Skill Finder

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