Json schema validator

Skill baronguyen001/ai-automation-skills/skills/json-schema-validator

Validate a dict/JSON payload against a useful subset of JSON Schema (type, required, properties, items, enum, min/max, length) with zero dependencies, returning readable errors. Use when the user wants to validate a webhook payload, API response, or config against a schema, or gate bad data before processing - without adding the jsonschema package.From its SKILL.md

Install

npx -y skills add baronguyen001/ai-automation-skills --skill json-schema-validator

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One thing to look at

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SKILL.md

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JSON Schema Validator (zero-dep)

Use this skill to gate untrusted JSON - a webhook body, an API response, a config file - before your pipeline acts on it, without pulling in the jsonschema package. It walks a schema subset (type, required, properties, items, enum, minimum/maximum, minLength/maxLength) and returns a list of human-readable error strings, so you can log exactly what was wrong and skip the bad record instead of crashing three functions deep.

When to invoke

User says: "validate this payload", "check the webhook body matches a schema", "reject malformed records", "validate config against a schema".
A pipeline ingests external JSON and currently trusts its shape.

When NOT to invoke

You need full Draft 2020-12 features ($ref, allOf, patternProperties, formats) - install jsonschema.
The data is already typed by a model layer (e.g. Pydantic) - validate there.

Concrete example

User input:

Only accept events shaped like {type: str in [buy,sell], amount: number >= 0}.

Output:

# Copy assets/validate.py into your project, then:
from validate import validate, is_valid

schema = {
    "type": "object",
    "required": ["type", "amount"],
    "properties": {
        "type": {"enum": ["buy", "sell"]},
        "amount": {"type": "number", "minimum": 0},
    },
}

errors = validate({"type": "hold", "amount": -3}, schema)
# ["$.type: 'hold' not in enum ['buy', 'sell']", "$.amount: -3 < minimum 0"]
if not is_valid(event, schema):
    skip(event)

Errors carry a JSON-path-ish location ($.amount, $.items[2].id) so logs point straight at the bad field.

Pattern to apply

Check type first; on a mismatch, stop descending (deeper checks would be noise).
Accumulate errors instead of raising, so one pass reports every problem.
Treat bool as distinct from int/number - a common JSON validation bug.
Use it as a gate: if not is_valid(...): skip/quarantine before any side effects.

Reference: assets/validate.py.

Source

Distilled from webhook + API-ingestion work in the author's automations. v1.0.0. See also: [[webhook-receiver]], [[env-config-loader]], [[pipeline-orchestrator]].

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What ships with it: 1 file

2.9 KB alongside SKILL.md, 1 of them executable

assets/

validate.pyruns2.9 KB