Use Case Governance Classifier
Submits an AI use case via webhook to screen for risk, classify it as normal, elevated, or prohibited, generate a checklist.
HR and recruiting teamsops and IT teams
What it does
You submit AI use cases via webhook to instantly get screened for risk and classified as normal, elevated, or prohibited with a generated checklist. The system automatically logs your data in Supabase and sends email notifications so you always have a clear audit trail.
Step by step
- Set up a webhook endpoint in your backend framework to accept POST requests from the submission form.
- Configure Supabase client credentials and define the schema for the use_case_requests table including status and risk_score columns.
- Implement the email service integration using the Send Email tool with predefined templates for each classification outcome.
Where the LLM does the work
- Prompt the Anthropic model to analyze the submitted use case description and determine if it falls into normal, elevated, or prohibited categories based on defined risk criteria.
- Generate a customized oversight checklist tailored to the specific risks identified in the submission rather than using static templates.
Watch out for
Supabase row-level security policies might block writes if not configured correctly so verify the service role key permissions before deployment.
Email notifications may fail silently if the recipient address is invalid so implement a retry mechanism with error logging.
LLM outputs can vary in format which breaks downstream parsing so enforce a strict JSON schema response structure.
Tools that fit
The agent brief
Everything your agent needs, including the gotchas. Copy it and go.
You are helping me build the following AI agent workflow. ## Goal Use Case Governance Classifier: Submits an AI use case via webhook to screen for risk, classify it as normal, elevated, or prohibited, generate a checklist. ## Specification - What it does: You submit AI use cases via webhook to instantly get screened for risk and classified as normal, elevated, or prohibited with a generated checklist. The system automatically logs your data in Supabase and sends email notifications so you always have a clear audit trail. - Trigger: Triggered by an event (Event · on webhook submission) - Autonomy: Fully hands-off - Expected setup effort: about an afternoon - Tools/services involved: - Anthropic: AI risk screening and classification - Supabase: Logging AI use case records - Send Email: Sending notifications to stakeholders ## Known pitfalls, handle each one explicitly in your implementation 1. Supabase row-level security policies might block writes if not configured correctly so verify the service role key permissions before deployment. 2. Email notifications may fail silently if the recipient address is invalid so implement a retry mechanism with error logging. 3. LLM outputs can vary in format which breaks downstream parsing so enforce a strict JSON schema response structure. ## Reference implementation https://n8n.io/workflows/15879 (workflow template) Fetch and inspect this before building. If it matches my stack, adapt it; if not, rebuild the pattern with my tools. ## Process requirements 1. Before building: ask me which of the listed tools I actually use and what my platform is (n8n / Make / code / other). Do not assume. 2. Adapt the pattern to my answers; do not force the reference stack. 3. Address every pitfall above; tell me how you handled each. 4. Provide a test plan I can run before letting this touch real data. 5. Ask before any step that sends messages, modifies data, or spends money. Source: https://usecasesforagents.com/use-case/ai-use-case-governance-classifier/ via usecasesforagents.com
Frequently asked questions
Can I use a different LLM than Anthropic?
Yes. Anthropic is only the example LLM in this recipe. The same flow works with Cohere, DeepSeek, Google Gemini and Google Vertex AI. Swap the LLM connection and keep the rest of the setup as written.
Want this running in your business?
This is what I do. I design and build AI agents like this one, and keep them running. If you want it set up for your team instead of doing it yourself, get in touch.
Who it's for
Built for HR and recruiting teams who need a repeatable first pass, not a one-off.
Ops-IT teams triaging their own internal requests get the same pattern, different queue.