Recommendations

SkillKit analyzes your project and suggests relevant skills.

Get Recommendations

skillkit recommend

Output:

Project: my-app (Next.js + TypeScript + Tailwind)

Recommended Skills:
  92% vercel-react-best-practices
  87% tailwind-v4-patterns
  85% nextjs-app-router

Filters

skillkit recommend --search "auth"
skillkit recommend --category security
skillkit recommend --min-score 80

Explainable Recommendations

See WHY skills match your project:

skillkit recommend --explain

Output:

vercel-react-best-practices (Score: 92)
├── Matched: React, TypeScript, Next.js
├── Your stack: Next.js 14, React 18
└── Path: Frontend > React > Best Practices

LLM-Based Reasoning

Use reasoning-based discovery for complex queries:

skillkit recommend --reasoning

This uses an LLM to traverse the skill taxonomy and find the most relevant skills based on semantic understanding.

How It Works

The engine analyzes:

Project structure - Frameworks, languages, tools
Dependencies - package.json, requirements.txt
File patterns - Code patterns in your codebase

Scoring

Scores based on:

Stack match
Quality score (0-100)
Popularity
Task relevance

Programmatic API

import {
  RecommendationEngine,
  ReasoningRecommendationEngine,
  analyzeProject
} from '@skillkit/core'

// Basic recommendations
const engine = new RecommendationEngine()
const profile = await analyzeProject('./my-project')
const recs = engine.recommend(profile)

// With reasoning and explanations
const reasoningEngine = new ReasoningRecommendationEngine()
await reasoningEngine.initReasoning()
const explained = await reasoningEngine.recommendWithReasoning(profile, {
  reasoning: true,
  explain: true
})

Recommendations

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