input-validation

input-validation is a skill for Claude Code, Codex from jdmorag97-rgb/DDC_Skills_for_AI_Agents_in_Construction. It costs 29 tokens per session (4,394 once invoked), scanned A, a copy of input-validation, MIT.

A validation tool for checking construction information before it is processed. It reviews estimates, schedules, building-model data, and field reports using construction-specific rules.

In plain words
What is it for?
Use it to check cost estimates, schedules, BIM exports, and field data for missing, invalid, or inconsistent values.
Why use it?
Incorrect or incomplete inputs can produce unreliable project results. It flags errors and warnings early so they can be reviewed before processing continues.

Skill for Claude CodeCodex

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

Good fit Use it to check cost estimates, schedules, BIM exports, and field data for missing, invalid, or inconsistent values.

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

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

Your own site · 80×15
<a href="https://agentmods.dev/skills/jdmorag97-rgb/ddc_skills_for_ai_agents_in_construction/input-validation"><img src="https://agentmods.dev/badge/skills/jdmorag97-rgb/ddc_skills_for_ai_agents_in_construction/input-validation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 29 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,394 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 $0.00029 $0.04394
Opus 5 $0.00015 $0.02197
Sonnet 5 $0.00006 $0.00879
Haiku 4.5 $0.00003 $0.00439

Measured 9d ago against content hash 166a54af3147, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

input-validation 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 input-validation — 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/Data-Validation/input-validation/SKILL.md · 501 lines

How it starts

The opening of the file, as written. The whole thing — 501 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Input Validation for Construction Data

Overview

Validate incoming construction data before processing to catch errors early. Domain-specific validation rules for estimates, schedules, BIM exports, and field data.

Validation Framework

Core Validator Class

from dataclasses import dataclass, field
from typing import List, Dict, Any, Callable, Optional
from enum import Enum
import re
from datetime import datetime

class ValidationSeverity(Enum):
    ERROR = "error"      # Must fix, blocks processing
    WARNING = "warning"  # Should review, allows processing
    INFO = "info"        # FYI, no action needed

@dataclass
class ValidationIssue:
    field: str
    message: str
    severity: ValidationSeverity
    value: Any = None
    suggestion: str = None

@dataclass
class ValidationResult:
    is_valid: bool
    issues: List[ValidationIssue] = field(default_factory=list)

    def add_error(self, field: str, message: str, value: Any = None, suggestion: str = None):
        self.issues.append(ValidationIssue(field, message, ValidationSeverity.ERROR, value, suggestion))
        self.is_valid = False

    def add_warning(self, field: str, message: str, value: Any = None, suggestion: str = None):
        self.issues.append(ValidationIssue(field, message, ValidationSeverity.WARNING, value, suggestion))

    def add_info(self, field: str, message: str, value: Any = None):
        self.issues.append(ValidationIssue(field, message, ValidationSeverity.INFO, value))

    @property
    def errors(self) -> List[ValidationIssue]:
        return [i for i in self.issues if i.severity == ValidationSeverity.ERROR]

    @property
    def warnings(self) -> List[ValidationIssue]:
        return [i for i in self.issues if i.severity == ValidationSeverity.WARNING]

    def to_report(self) -> str:
        lines = ["VALIDATION REPORT", "=" * 50]
        lines.append(f"Status: {'PASSED' if self.is_valid else 'FAILED'}")
        lines.append(f"Errors: {len(self.errors)}, Warnings: {len(self.warnings)}")
        lines.append("")

        for issue in self.issues:
            icon = "❌" if issue.severity == ValidationSeverity.ERROR else "⚠️" if issue.severity == ValidationSeverity.WARNING else "ℹ️"
            lines.append(f"{icon} [{issue.field}] {issue.message}")
            if issue.suggestion:
                lines.append(f"   Suggestion: {issue.suggestion}")

        return "\n".join(lines)

Read the full file on GitHub · 501 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 · 501 lines · 29 tokens per session scan A 166a54af3147

Subscribe to this mod's changes

input-validation 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 29 tokens to every session and 4,394 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to input-validation, differing in 0 lines, and is treated as a copy.

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