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---
name: prompt-engineering-few-shot-selection-cls
description: "Choose and order examples covering edge cases so the model generalizes instead of copying surface patterns."
---
# Select few-shot examples that move accuracy (Classification tasks)
> Choose and order examples covering edge cases so the model generalizes instead of copying surface patterns.
**Track:** 🤖 AI Engineering · **Domain:** Prompt Engineering · **Level:** intermediate · **~30 min**
**Who this is for:** AI Engineers, ML Engineers, LLM App Developers, Agent Builders
## When to Use This Skill
Choose and order examples covering edge cases so the model generalizes instead of copying surface patterns.
Use it whenever a matching task appears in conversation — the agent loads these instructions on demand.
## Steps
1. Cover each output field's edge cases once: empty, unicode, long input, ambiguity
2. Order examples easy-to-hard so difficulty ramps within context
3. Match example format byte-for-byte to the required output format
4. Prefer real production samples over invented ones
5. Rotate in failure cases you fixed, turning regressions into teachers
6. Measure: remove one example at a time, drop any whose removal costs nothing
7. Include one deliberately ambiguous item with the correct tie-break label
8. Balance classes in examples; imbalance biases predictions
## Common Pitfalls
- Six near-identical easy examples teaching style but not judgment
- Whitespace mismatches between examples and instructions
## Commands
**Install with skills CLI**
```bash
npx skills add aniruddhaadak80/skills --skill prompt-engineering-few-shot-selection-cls
```
**Install globally**
```bash
npx skills add aniruddhaadak80/skills --skill prompt-engineering-few-shot-selection-cls -g
```
---
Part of [aniruddhaadak80/skills](https://github.com/aniruddhaadak80/skills) · Browse all at https://skills.sh/aniruddhaadak80/skills