prompt-templates

prompt-templates is a skill for Claude Code, Codex from jdmorag97-rgb/DDC_Skills_for_AI_Agents_in_Construction. It costs 30 tokens per session (3,469 once invoked), scanned A, a copy of prompt-templates, MIT.

Reusable instructions for AI tasks in construction, such as estimating costs, analysing schedules, processing documents, and querying building-model data.

In plain words
What is it for?
Use them to create prompts for construction estimates, schedule analysis, document processing, and BIM queries.
Why use it?
They give the AI a consistent structure and require the needed inputs, which helps produce more predictable results.

Skill for Claude CodeCodex

Which agent this was written for is unclear — built for openclaw. Also seen: built for openclaw.

Good fit Use them to create prompts for construction estimates, schedule analysis, document processing, and BIM queries.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/jdmorag97-rgb/ddc_skills_for_ai_agents_in_construction/prompt-templates
Install

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.

Any agent
npx skills add jdmorag97-rgb/DDC_Skills_for_AI_Agents_in_Construction --skill prompt-templates
Clone the repo
git clone --depth 1 https://github.com/jdmorag97-rgb/DDC_Skills_for_AI_Agents_in_Construction

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for prompt-templates

README.md
[![agentmods](https://agentmods.dev/badge/skills/jdmorag97-rgb/ddc_skills_for_ai_agents_in_construction/prompt-templates/github.svg)](https://agentmods.dev/skills/jdmorag97-rgb/ddc_skills_for_ai_agents_in_construction/prompt-templates)
Your own site
<a href="https://agentmods.dev/skills/jdmorag97-rgb/ddc_skills_for_ai_agents_in_construction/prompt-templates"><img src="https://agentmods.dev/badge/skills/jdmorag97-rgb/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.

agentmods 80×15 button for prompt-templates

Your own site · 80×15
<a href="https://agentmods.dev/skills/jdmorag97-rgb/ddc_skills_for_ai_agents_in_construction/prompt-templates"><img src="https://agentmods.dev/badge/skills/jdmorag97-rgb/ddc_skills_for_ai_agents_in_construction/prompt-templates.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 30 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,469 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 100% copy Near-identical to another mod in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured 9d ago against content hash 971934b22cdd, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

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.

Origin

This is a copy

100% identical to prompt-templates — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

4_DDC_Curated/Prompt-Engineering/prompt-templates/SKILL.md · 576 lines

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)

Read the full file on GitHub · 576 lines

Files

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.

Changes

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.

  1. 9d ago First seen · 576 lines · 30 tokens per session scan A 971934b22cdd

Subscribe to this mod's changes

prompt-templates is a skill published in the GitHub repository jdmorag97-rgb/DDC_Skills_for_AI_Agents_in_Construction (2 stars, last pushed 6mo 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. It is 100% identical to prompt-templates, differing in 0 lines, and is treated as a copy.

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