> ## Documentation Index > Fetch the complete documentation index at: https://docs.befailproof.ai/llms.txt > Use this file to discover all available pages before exploring further. # Set up an audit > Define an audit goal, session population, and evidence context. The quality of an audit starts with its scope. A broad request such as “find problems” produces less useful results than a concrete failure question. ## Configure the audit 1. Go to **Analyze → Audits → New audit** and enter the name and description. 2. Set the cadence, time window, agent/environment scope, ignored errors, sensitivity, and maximum findings. 3. In **agents**, add or review agent context, then add the operator brief and any public HTTPS reference URLs. 4. Choose notification channels and select **create audit**. The first run queues immediately. The new audit form with name, description, cadence, window, environment and agent scope, ignored errors, analysis settings, brief, reference pages, and notification channels. ```bash theme={null} fp audits create checkout-reliability \ --description "Find checkout failures that agents do not recover from" \ --scope '{"environments":["production"],"agent_ids":["checkout-agent"]}' \ --schedule-interval-secs 86400 \ --window-mode since_last \ --sensitivity medium \ --text-file ./checkout-audit-brief.txt \ --url https://runbooks.example.com/checkout ``` The first run queues immediately. Include the brief and reference URLs during creation so that run receives them. See the complete [`fp audits create` reference](/reference/cloud-cli#audits). Start with a known failed session and several normal sessions. This gives the audit both a positive example and a comparison set. Audit context is stored as its own resource so editing an audit does not accidentally remove the reference material.