skill-finder
- Repo stars 402
- Author repo affiliate-skills
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:
- Skill names and slugs (exact match → top priority)
- Skill descriptions (keyword overlap)
- Stage labels and descriptions (if user is browsing by stage)
- 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:
- Direct name/slug match
- Description keyword match count
- 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
- Matching Skills — table with skill name, stage, description, and relevance
- How to Use — for each top match, show the exact prompt to invoke it
- 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-reportto track ongoing revenue
Do This Right Now (15 min)
- Copy the first recommended prompt from the Recommended Path section and run it immediately
- Don't skip steps — the recommended path is ordered for a reason. S1 before S2, S2 before S5
- Set a goal: earn your first commission within 14 days by running one skill per day
- 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_skillroutes 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- Fluxly category
- Other
- Author-declared agents
- No explicit declaration found; this is not inferred or tested compatibility
- Static check
- 88 / 100 · heuristic scan, not runtime safety proof
- Author / version / license
- @Affitor · no license declared
- Fluxly token estimate
- Lean
- Fluxly setup estimate
- Plug-and-play
- External API key
- No requirement detected
- Detected OS requirements
- Unspecified
- Runtime requirements
- Unspecified
- Detected file/system behavior
-
- Read-only
- Write / modify
- Detected network behavior
- Local-only
- Install commands
- None (reference only)
Profile is derived at build time from SKILL.md and install vectors. Subject to drift from author intent.
Heads up: 未限定 allowed-tools,默认拥有全部工具权限。
# Step 3: Rank Results
1. Direct name/slug match
2. Description keyword match count
3. Stage alignment with user's apparent funnel position Workflow
Read registry.json from the repository root (or from conversation context if already loaded). Parse all skills with their stage, name, slug, and description.
Match the user's query against: Skill names and slugs (exact match → top priority) Skill descriptions (keyword overlap)
Rank matches by relevance: Direct name/slug match Description keyword match count
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)"
Present top 3-5 matching skills with: Skill name and stage What it does (one sentence)
# 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:
… Author text anchors workflow facts; Fluxly only indexes current sections, terms, files, and commands.
sections -> Stage → When to Use → Input Schema → Workflow → Step 1: Load Skill Catalog → Step 2: Match Query to Skills
terms -> Matching Skills · How to Use · Recommended Path · Empty query · No matches found · Too broad query ("everything") · User · Action
files/cmd -> registry.json · query · seo-audit · affiliate-blog-builder · stagefilter · comparison-post-writer · viral-post-writer · affiliate-program-search
body sha256 -> 3bda92ee0fc2
Decide Fit First
Design Intent
How To Use It
Boundaries And Review