Customer Artifact Generation with Claude Code: Result JSON Schema
A production playbook for customer artifact generation in cross-industry operations using Claude Code: result json schema, run-scoped inputs, logs, typed results, and artifacts.
Audience: Product teams delivering reports or spreadsheets
The problem
Product teams delivering reports or spreadsheets need customer artifact generation to run repeatedly against source data, templates, and delivery requirements. In cross-industry operations, the pain is not one good answer; it is repeatability, auditability, exception handling, and evidence that survives handoff.
Implementation path
Define the outer result contract once, let the customer artifact generation skill own body.data, and reject terminal output that does not match the expected schema.
Tradeoffs and failure modes
Schema enforcement adds upfront design work, but removes prompt parsing from the product surface. For customer artifact generation, the practical test is whether a second run can be debugged, retried, and consumed by a product without reading the raw agent transcript.
Result shape
{
"schema_version": "argo.result.v1",
"summary": "customer artifact generation completed",
"body": { "type": "artifact_generation", "data": {}, "exceptions": [] },
"artifacts": []
}
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