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Skill Finder

Organization
Affitor
skill-finder

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".

Overview

PublisherAffitor
Repositoryaffiliate-skills
Skill nameskill-finder
Stars
705
Forks
209
Bundled files
1
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by Affitor on GitHub. Read the source before you install it.

Installation

Install the Skill Finder AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/Affitor/affiliate-skills/tree/main/skills/meta/skill-finder
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Affitor/affiliate-skills.git /tmp/affiliate-skills
mkdir -p .claude/skills
cp -r /tmp/affiliate-skills/skills/meta/skill-finder .claude/skills/skill-finder
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Skill Finder in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Skill Finder on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Skill Finder is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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

yaml
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

yaml
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

Revenue & Action Plan

Expected Outcomes

  • Revenue potential: The fastest path to your first commission is using the right skill at the right time. Skill Finder saves you hours of guessing — it matches your current situation to the exact workflow that generates revenue. Affiliates who follow a structured skill sequence report 3x faster time-to-first-commission
  • Benchmark: The typical path to first commission: S1 (find product, 30 min) → S2 (create content, 1 hour) → S5 (distribute, 30 min) = first affiliate link live in 2 hours. First commission typically arrives within 7-14 days
  • Key metric to track: Time-to-first-commission. How long from "I started" to "I earned my first dollar"? Use performance-report to track ongoing revenue

Do This Right Now (15 min)

  1. Copy the first recommended prompt from the Recommended Path section and run it immediately
  2. Don't skip steps — the recommended path is ordered for a reason. S1 before S2, S2 before S5
  3. Set a goal: earn your first commission within 14 days by running one skill per day
  4. Bookmark this skill — come back whenever you're unsure what to do next

Track Your Results

After running 3-5 skills in sequence: do you have a live affiliate link? Is it getting clicks? If yes, you're on the path. If no, re-run Skill Finder with a more specific goal ("I have a blog but no traffic" vs "I'm starting from zero").

Next step — run the first skill in your Recommended Path!

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

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Skill Finder AI skill do?

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".

Why use Skill Finder on TypingMind?

Because you install it once and use it with any model. Skill Finder is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Skill Finder in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Affitor/affiliate-skills/tree/main/skills/meta/skill-finder. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Skill Finder?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Skill Finder?

As many as you like. As long as a model supports skills, you can use Skill Finder with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Skill Finder AI skill free?

Yes. It is published on GitHub by Affitor under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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