navveenb Model Recommender Skill
Task-to-Tier Mapping
Tier 1: Small / Fast (Haiku, GPT-4o-mini, Gemini Flash)
- Classification (spam/not-spam, category assignment)
- Entity extraction (names, dates, emails)
- Sentiment analysis
- Routing decisions
- Simple formatting (JSON restructuring, template filling)
- Yes/no judgments, slot filling
Tier 2: Mid-Range (Sonnet, GPT-4o, Gemini Pro)
- Summarization (single document)
- Translation
- Simple code generation (known patterns)
- Structured data extraction from complex documents
- Q&A with provided context
- Email/message drafting
Tier 3: Frontier (Opus, GPT-4/o1, Gemini Ultra)
- Complex multi-step reasoning
- Novel problem solving
- Nuanced creative writing
- Multi-document synthesis
- Architectural planning
- Novel/complex code generation
Decision Rules
- When in doubt, start small — default to Tier 1.
- Classification is ALWAYS Tier 1.
- Extraction is almost always Tier 1.
- Summarization is Tier 2 (unless multi-document → Tier 3).
- Code generation: boilerplate = Tier 1, standard = Tier 2, novel = Tier 3.
- If a task could be done with regex/rules → no LLM at all.
Red Flags
- Frontier model for classification → should be Tier 1
- Frontier model for formatting/extraction → should be Tier 1
- Frontier model for simple summarization → should be Tier 2
- Any LLM call for a deterministic task → should be code, not LLM