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 jdmorag97-rgb/DDC_Skills_for_AI_Agents_in_Construction --skill input-validationgit clone --depth 1 https://github.com/jdmorag97-rgb/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/jdmorag97-rgb/ddc_skills_for_ai_agents_in_construction/input-validation)<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.
<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>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 | $0.00029 | $0.04394 |
| Opus 5 | $0.00015 | $0.02197 |
| Sonnet 5 | $0.00006 | $0.00879 |
| Haiku 4.5 | $0.00003 | $0.00439 |
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.
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.
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)
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 · 501 lines · 29 tokens per session scan A 166a54af3147
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.
Other skills, from other repositories
systemic-issue-triage
Trigger: new issue, bug report, triage, backlog, issue flood, community report, root cause, dead-end, blocked user. Attack issues by root class, never one-by-one; fixes must shrink the system, not grow it.
triage-issue
Intelligently triage bug reports and error messages by searching for duplicates in Jira and offering to create new issues or add comments to existing ones. When an agent needs to: (1) Triage a bug report or error message, (2) Check if an issue is a duplicate, (3) Find similar past issues, (4) Create a new bug ticket…
bug-triage
Read all open bugs in production/qa/bugs/, re-evaluate priority vs. severity, assign to sprints, surface systemic trends, and produce a triage report. Run at sprint start or when the bug count grows enough to need re-prioritization.
browse-flows
Browse Power Automate environments and flows interactively. Use when the user wants to browse, list, or explore their flows and environments.
operating-cadence
Designs the rhythm an organization runs on — which reviews happen weekly, monthly and quarterly, what each one decides, who owns the numbers presented, and how a signal at the front line reaches the people who can act on it. Use this to set up a management operating system, fix a meeting calendar that produces no…
status
Display current FIRE project status and validate integrity of intents, work items, and runs.