Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill prompt-templatesgit clone --depth 1 https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_ConstructionWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction/prompt-templates)<a href="https://agentmods.dev/skills/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction/prompt-templates"><img src="https://agentmods.dev/badge/skills/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction/prompt-templates/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction/prompt-templates"><img src="https://agentmods.dev/badge/skills/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction/prompt-templates.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high System Prompt Leakage · line 48 Skill contains instructions that could directly expose system prompts, internal rules, or hidden instructions to users or external parties.Fix: Remove any instructions that reveal, print, or output system prompts or internal rules. System instructions should never be exposed to end users.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00030 | $0.03469 |
| Opus 5 | $0.00015 | $0.01734 |
| Sonnet 5 | $0.00006 | $0.00694 |
| Haiku 4.5 | $0.00003 | $0.00347 |
Grade A, and why
prompt-templates scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
1 near-identical copy found in the catalogue:
- prompt-templates — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 576 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Prompt Templates for Construction AI
Overview
Structured, reusable prompt templates optimized for construction industry AI tasks. These templates ensure consistent, high-quality outputs for cost estimation, schedule analysis, document processing, and BIM data queries.
Template Framework
Base Template Structure
from dataclasses import dataclass, field
from typing import Dict, Any, List, Optional
from string import Template
import json
@dataclass
class PromptTemplate:
name: str
description: str
template: str
input_variables: List[str]
output_format: Optional[str] = None
examples: List[Dict[str, Any]] = field(default_factory=list)
category: str = "general"
version: str = "1.0"
def format(self, **kwargs) -> str:
"""Format template with provided variables."""
# Validate all required variables are provided
missing = [v for v in self.input_variables if v not in kwargs]
if missing:
raise ValueError(f"Missing required variables: {missing}")
# Format template
prompt = Template(self.template).safe_substitute(**kwargs)
# Add output format if specified
if self.output_format:
prompt += f"\n\nOutput Format:\n{self.output_format}"
return prompt
def with_examples(self, n: int = 2) -> str:
"""Return template with few-shot examples."""
examples_text = ""
for i, ex in enumerate(self.examples[:n], 1):
examples_text += f"\nExample {i}:\n"
examples_text += f"Input: {ex.get('input', '')}\n"
examples_text += f"Output: {ex.get('output', '')}\n"
return f"{examples_text}\n{self.template}"
class ConstructionPromptLibrary:
"""Library of construction-specific prompt templates."""
def __init__(self):
self.templates: Dict[str, PromptTemplate] = {}
self._register_defaults()
def register(self, template: PromptTemplate):
self.templates[template.name] = template
def get(self, name: str) -> Optional[PromptTemplate]:
return self.templates.get(name)
def list_by_category(self, category: str) -> List[PromptTemplate]:
return [t for t in self.templates.values() if t.category == category]
def _register_defaults(self):
# Register all default templates
for template in DEFAULT_TEMPLATES:
self.register(template)
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 576 lines · 30 tokens per session scan A 971934b22cdd
prompt-templates is a skill published in the GitHub repository datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction (310 stars, last pushed 21d ago), licensed MIT. It adds 30 tokens to every session and 3,469 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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