Running CrewScore as a service, AI Evaluation Observability

CrewScore Agency Implementation, Prompt Safety Audits for Client Delivery

Learn how to integrate CrewScore's 23-point guardrail audits into your AI agent delivery workflow, from initial client prompt review through CI/CD regression protection. This course teaches agencies how to position prompt safety verification as a productized service, document written controls for compliance, and automate guardrail checks without exposing sensitive client instructions.

Open the decision record for CrewScore

What does running CrewScore for clients commit you to?

Published figures for this service. Blank fields are not published.

Monthly tool cost
Not published
Time to first value
hours
Payback
Not modeled
Guided implementation
8 hours

Is CrewScore worth running as a client service?

CrewScore is an open-source, local-first guardrail checker that fits cleanly into an adoption/resell service for agencies already building AI agents, with setup measured in hours. What remains unknown is client willingness to pay, delivery labor per engagement, and whether recurring CI regression alerts sustain retention, none of which the vendor data establishes.

An agency-fit judgement for reselling this service. It is separate from the tool description on the decision record.

Before you start

What has to be in place before the first client engagement.

Tools and subscriptions

  • CrewScore browser checker for local prompt scoring (no upload, no signup, no API key)
  • CrewScore CLI installed via `pip install crewscore`
  • CrewScore GitHub Action (`uses: shmindmaster/crewscore@v2`) for CI/CD integration
  • Access to client AI instruction sources: ChatGPT, Claude, Cursor, or local files
  • GitHub repository access for importing public GitHub blob or raw files and emitting SARIF findings

People and inputs

  • Review of the 23 public guardrail controls and published methodology documentation before client-facing claims
  • A written scope statement clarifying that CrewScore measures written-control presence, not runtime safety enforcement
  • A SARIF consumption path in each client's code scanning or security tooling
  • At least one client AI agent prompt set to use as a validation case

Estimated investment: Vendor cost is open-source; no plan price is published. The only modeled investment is internal labor to install the CLI, wire the GitHub Action, and review the public control catalog. Any client-facing fee must be set by your own labor estimate, no vendor pricing basis exists.

Included with the course

7 working documents for delivering this service.

  • Client Prompt Audit Checklist - 23 Safety Controlschecklist
  • CrewScore CI/CD Integration Setup Guideguide
  • Prompt Safety Audit Report Templatetemplate
  • Written Control Regression Prevention SOPsop
  • Multi-Model Prompt Import Workflowworksheet
  • SARIF Findings Documentation for Clientstemplate
  • Guardrail Audit Pricing & Packaging Worksheetworksheet

Listed by name. These documents are not yet published as individual downloads.