{"schemaVersion":"1.0","source":"The Workflow Finder","sourceUrl":"https://www.theworkflowfinder.com","license":"Free to use with attribution and a link to the cited page","generated":"2026-08-28","workflow":{"title":"Evaluate an AI Agent Before Trusting It","slug":"evaluate-an-ai-agent-before-trusting-it","url":"https://www.theworkflowfinder.com/workflows/evaluate-an-ai-agent-before-trusting-it","description":"Build a repeatable test before you deploy the agent, so a model update, a prompt tweak, or a tool integration change doesn't silently break its judgment without anyone noticing.","difficulty":"Advanced","timeEstimate":"3-5 hours, one-time setup","schemaDuration":"PT5H","expectedResult":"A fixture-task test suite with a scored baseline that re-runs automatically whenever the agent's model, prompt, or tools change, flagging any drop in quality before it reaches real users.","tags":["Agents","Evaluation","Quality Assurance"]},"steps":[{"position":1,"title":"Build a Fixture Task Set From Real Cases","instructions":"Collect 15-25 representative tasks the agent will actually face, each with a known-correct answer or an acceptable range, drawn from real historical cases rather than invented scenarios. This fixture set is the ground truth everything else in this workflow measures against -- a fixture set built from convenient, easy examples will pass every time and tell you nothing.","input":"Workflow inputs: the topic, goal, or raw materials the user is starting from.","output":"Handoff artifact consumed by Step 2 (\"Add Adversarial and Edge Cases With Giskard\").","ioProvenance":{"input":"structural","output":"structural"},"toolSlots":[]},{"position":2,"title":"Add Adversarial and Edge Cases With Giskard","instructions":"Use Giskard's automated test generation to add adversarial inputs to the fixture set: prompt injections, off-topic requests, ambiguous phrasing, and inputs designed to surface hallucinations. A friendly test set only ever tells you the agent works when everything goes right; this is what catches it before a real user does.","input":"Output of Step 1 (\"Build a Fixture Task Set From Real Cases\").","output":"Handoff artifact consumed by Step 3 (\"Score the Agent Against the Full Set in Braintrust\").","ioProvenance":{"input":"structural","output":"structural"},"toolSlots":[{"slug":"giskard","name":"Giskard","url":"https://www.theworkflowfinder.com/tools/giskard","category":"Developer Tools","pricing":"freemium","capabilities":["Code review","Debugging assistance"]}]},{"position":3,"title":"Score the Agent Against the Full Set in Braintrust","instructions":"Run the fixture set through the agent using Braintrust, scoring each output against defined criteria, correctness, whether it called the right tool, whether the output format is usable downstream, instead of eyeballing a handful of outputs and calling it good.","input":"Output of Step 2 (\"Add Adversarial and Edge Cases With Giskard\").","output":"Handoff artifact consumed by Step 4 (\"Set a Regression Baseline\").","ioProvenance":{"input":"structural","output":"structural"},"toolSlots":[{"slug":"braintrust","name":"Braintrust","url":"https://www.theworkflowfinder.com/tools/braintrust","category":"Developer Tools","pricing":"freemium","capabilities":["API integration"]}]},{"position":4,"title":"Set a Regression Baseline","instructions":"Save the current pass rate as the baseline and re-run the full fixture set every time the underlying model updates, the prompt changes, or a connected tool's API changes. Wire this to run automatically rather than relying on remembering to do it by hand -- a manual step is a step that eventually gets skipped right before the change that actually breaks something.","input":"Output of Step 3 (\"Score the Agent Against the Full Set in Braintrust\").","output":"Handoff artifact consumed by Step 5 (\"Log Every Failure With Enough Context to Debug It\").","ioProvenance":{"input":"structural","output":"structural"},"toolSlots":[{"slug":"braintrust","name":"Braintrust","url":"https://www.theworkflowfinder.com/tools/braintrust","category":"Developer Tools","pricing":"freemium","capabilities":["API integration"]}]},{"position":5,"title":"Log Every Failure With Enough Context to Debug It","instructions":"Every failing case gets logged with the input, the agent's actual output, the expected output, and its tool calls if visible, enough for a person to diagnose what went wrong, not just a pass or fail flag with no trail behind it.","input":"Output of Step 4 (\"Set a Regression Baseline\").","output":"Final workflow output: A fixture-task test suite with a scored baseline that re-runs automatically whenever the agent's model, prompt, or tools change, flagging any drop in quality before it reaches real users.","ioProvenance":{"input":"structural","output":"structural"},"toolSlots":[]}]}