skill-finder
- Repo stars 402
- Author updated Live
- Author repo affiliate-skills
- Domain
- Other
- Compatible agents
-
- Claude Code
- Cursor
- Cline
- Codex
- Windsurf
- Gemini CLI
- +20
- Trust score
- 88 / 100 · community maintained
- Author / version / license
- @Affitor · no license declared
- Token usage
- Lean
- Setup complexity
- Plug-and-play
- External API key
- Not required
- Operating systems
- Unspecified (assume cross-platform)
- Runtime requirements
- No special requirements
- Permissions
-
- Read-only
- Write / modify
- Network behavior
- Local-only
- Install commands
- 26 variants
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。
---
name: skill-finder
description: > Search and discover Affitor skills by task, stage, keyword, or natural language goal. Returns…
category: other
runtime: no special runtime
---
# skill-finder output preview
## PART A: Task fit
- Use case: > 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. runs entirely locally. Works with Claude Code, Cursor, Cline and 23 more..
- Inputs: target material, constraints, expected output, and acceptance criteria.
- Evidence boundary: follow “Stage / When to Use / Input Schema” and do not present inference as author intent.
## PART B: Execution result
- **01** The card summarizes the use case; runtime output centers on “> 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. runs entirely locally. Works with Claude Code, Cursor, Cline and 23 more.”.
- **02** When the source has headings, the agent prioritizes “Stage / When to Use / Input Schema” so the result follows the author’s structure.
- **03** Typical output includes task judgment, concrete steps, required commands or file edits, validation, and follow-up options.
- **04** Risk context follows the fingerprint: read files, write/modify files; mostly runs locally; usually needs no extra API key.
## Running Rules
- read files, write/modify files; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding scope.
- Return the result, validation criteria, and next iteration options. The source does not require a stable slash command. After installation, invoke the skill by name and describe the task.
Name target files or source material, expected output, forbidden changes, and whether network or shell access is allowed. Permission fingerprint: read files, write/modify files.
Start with a small task and check whether the result follows “Stage / When to Use / Input Schema”. Inspect diffs, logs, previews, or tests before expanding scope.
Confirm the final output includes a concrete result, evidence, and next action. If it stays generic, tighten inputs, boundaries, and acceptance criteria.
---
name: skill-finder
description: > Search and discover Affitor skills by task, stage, keyword, or natural language goal. Returns…
category: other
source: Affitor/affiliate-skills
---
# skill-finder
## When to use
- > Search and discover Affitor skills by task, stage, keyword, or natural language goal. Returns a ranked list of match…
- Use it when the task has clear inputs, repeatable steps, and validation criteria.
## What to provide
- Target material, scope, expected result, and forbidden changes.
- Whether network, commands, file writes, or external services are allowed.
## Execution rules
- Organize steps around “Stage / When to Use / Input Schema” and keep inference separate from source facts.
- read files, write/modify files; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding the task.
## Output requirements
- Return the deliverable, key evidence, validation method, and next action.
- Mark missing information as unknown; do not invent commands, platforms, or dependencies. The author source anchors workflow facts; repository files anchor sources and commands; Fluxly only adds fit, limitations, and quality judgment.
skill "skill-finder" {
input -> user goal + target files + boundaries + acceptance criteria
context -> Stage / When to Use / Input Schema
rules -> SKILL.md triggers / order / output contract
runtime -> no special runtime | read files, write/modify files | mostly runs locally
guardrails -> usually needs no extra API key + small-sample validation + diff/log review
output -> copyable result + checklist + next iteration
} 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
Decide Fit First
Design Intent
How To Use It
Boundaries And Review