Curated few-shot examples for construction AI tasks: classification, extraction, analysis. Domain-specific examples for improved LLM performance.
SkillScore59Maintained
Automatic
◆AI Engineer pack
Last verified 8/23/2026
What it changes
Passed 13 of 22 test cases with the skill, and 5 of 22 without it.
Without skill23%
With skill59%
Checks it passed that the model alone missed
The urgency is low
The urgency rating is critical
The rfi_type is field_condition
and 13 more in the full report
8 fixed5 passed either way9 still failing0 broke
Pass-rate lift
+36 pp
Tokens
+256%
Agent turns
0%
Response time
+4%
Model gemini-3.6-flashMeasured 8/23/2026v113 of 22 cases passed with skill
Tokens, turns and time describe resource use, not a dollar price.
See it in action
One of 8 test cases the skill fixed. Same model, same prompt, with and without the skill.
1 of 8
Prompt
What CSI MasterFormat division, section code, and title should be assigned to 'VCT flooring in corridors' in a few-shot example?
What was checked, without and with the skill
Checked
Without skill
With skill
The assigned CSI division is 09
Passed
Passed
The assigned CSI section is 09 65 00
Missed
Passed
The assigned CSI title is Resilient Flooring
Missed
Passed
case-15 · gemini-3.6-flash · 8/23/2026 · answers are capped and redacted
What's inside
The instructions your model reads when the skill loads.
SKILL.md635 linessingle file
Few-Shot Examples for Construction AI
Overview
Curated few-shot examples for construction industry AI tasks. These examples improve LLM performance by providing domain-specific context for classification, extraction, and analysis tasks.
Few-Shot Framework
Example Manager
from dataclasses import dataclass, field
from typing import List, Dict, Any, Optional
import json
import random
@dataclass
class FewShotExample:
input: str
output: str
explanation: Optional[str] = None
tags: List[str] = field(default_factory=list)
difficulty: str = "medium" # easy, medium, hard
source: str = ""
@dataclass
class ExampleSet:
name: str
description: str
task_type: str
examples: List[FewShotExample]
version: str = "1.0"
def get_examples(self, n: int = 3, difficulty: str = None) -> List[FewShotExample]:
"""Get n examples, optionally filtered by difficulty."""
filtered = self.examples
if difficulty:
filtered = [e for e in self.examples if e.difficulty == difficulty]
return filtered[:n]
Extract quantities from IFC/Revit models for quantity takeoff. Uses DDC converters to get element counts, areas, volumes, lengths with grouping and reporting.