Prompt Injection Red-Team Review with Claude Code: Result JSON Schema
A production playbook for prompt injection red-team review in cross-industry operations using Claude Code: result json schema, run-scoped inputs, logs, typed results, and artifacts.
Audience: AI security teams
The problem
AI security teams need prompt injection red-team review to run repeatedly against prompts, tool policies, transcripts, and suspicious inputs. 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 prompt injection red-team review 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 prompt injection red-team review, 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": "prompt injection red-team review completed",
"body": { "type": "red_team_prompt_review", "data": {}, "exceptions": [] },
"artifacts": []
}
Run this on Argo