data-validation
Validate Data with Pydantic and Zod
APIs and forms often drift when validation rules are copied between layers. This skill gives Claude, Codex, and Claude Code practical patterns for shared schemas, clear errors, and safer input handling.
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Review the Skillstore skill "data-validation" from https://skillstore.io/skills/awais68-data-validation.md and its manifest at https://skillstore.io/api/skills/awais68-data-validation/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.Your Agent should still show its plan and request any confirmation required by the security policy.
Agent-readable resources
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Test it
Using "data-validation". A developer asks for validation on a student creation form.
Expected outcome:
The response lists required fields, email and phone formats, grade limits, date checks, and matching backend and frontend schema responsibilities.
Using "data-validation". A team wants consistent validation errors across an API and React form.
Expected outcome:
The response explains how to map backend validation details to form fields and keep user messages clear.
Using "data-validation". A reviewer asks whether all external inputs are validated before database writes.
Expected outcome:
The response provides a concise checklist covering schema coverage, length limits, sanitization, server-side validation, and response models.
Security Audit
SafeAll static findings were adjudicated as false positives. Backticks appear in Markdown fences, TypeScript template literals, and inline documentation, while the fetch call targets a relative app route in example code. No prompt injection, exfiltration intent, or malicious behavior was found.
Risk Factors
⚙️ External commands (30)
🌐 Network access (1)
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APA citation
Awais68. (2026). data-validation security audit report (audit version 8) [Author version unspecified]. Skillstore. https://skillstore.io/skills/awais68-data-validation/audits/8BibTeX citation
@techreport{awais68-awais68-data-validation-2026,
author = {Awais68},
title = {data-validation security audit report (audit version 8)},
institution = {Skillstore},
year = {2026},
number = {8},
url = {https://skillstore.io/skills/awais68-data-validation/audits/8},
note = {Author version unspecified}
}CITATION.cff
cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "data-validation security audit report (audit version 8)"
version: "unspecified"
type: report
authors:
- name: "Awais68"
date-released: "2026-07-06"
url: "https://skillstore.io/skills/awais68-data-validation/audits/8"
identifiers:
- type: other
value: "skillstore:awais68-data-validation:audit:8"
description: "Skillstore immutable audit report identifier"
Skillstore Score
Why this score Evidence Confidence: HighWhat You Can Build
Design API request models
Create clear Pydantic schemas for create, update, response, pagination, and validation error payloads.
Validate frontend forms
Use Zod and React Hook Form to validate inputs before submit and show field-level errors.
Align frontend and backend contracts
Document shared constraints so teams keep field names, limits, formats, and error behavior consistent.
Try These Prompts
Create Pydantic and Zod validation schemas for this form: [fields]. Include required fields, length limits, and clear error messages.
Review my entity fields and design separate create, update, and response validation models. Explain which fields belong in each model.
Add validation rules that compare multiple fields for this workflow: [workflow]. Provide matching backend and frontend validation behavior.
Audit these API and form fields for validation gaps. Identify missing constraints, unsafe assumptions, inconsistent errors, and sanitization needs.
Best Practices
- Validate every external input on the backend, even when the frontend also validates it.
- Keep create, update, and output models separate to avoid leaking fields or accepting unsafe data.
- Define shared constants for limits and formats so frontend and backend rules stay aligned.
Avoid
- Do not trust client-only validation for database writes or privileged API actions.
- Do not reuse database models directly as public request or response schemas.
- Do not return vague validation errors when users need field-specific correction guidance.
Frequently Asked Questions
Does this skill generate complete application code?
Can it help with both Python and TypeScript?
Does it replace backend validation with frontend validation?
Can it handle custom business rules?
Does it include sanitization guidance?
Is this skill safe for Claude Code and Codex workflows?
Developer Details
Author
Awais68License
MIT
Skillstore revision
r1
Version notice
The author did not declare a version.
Ref
c4231f0153ccd2a2ed62274c5a372bf8f2386d3f
Maintenance freshness
7/18/2026
Usage
5 downloads · 195 views