{"id":58358,"date":"2026-08-12T16:01:47","date_gmt":"2026-08-12T06:01:47","guid":{"rendered":"https:\/\/www.cloudproinc.com.au\/index.php\/2026\/08\/12\/how-to-evaluate-groundedness-tool-accuracy-and-task-completion\/"},"modified":"2026-08-12T16:03:08","modified_gmt":"2026-08-12T06:03:08","slug":"how-to-evaluate-groundedness-tool-accuracy-and-task-completion","status":"publish","type":"post","link":"https:\/\/cloudproinc.azurewebsites.net\/index.php\/2026\/08\/12\/how-to-evaluate-groundedness-tool-accuracy-and-task-completion\/","title":{"rendered":"How to Evaluate Groundedness Tool Accuracy and Task Completion"},"content":{"rendered":"\n<p class=\"wp-block-paragraph\">In this blog post How to Evaluate Groundedness Tool Accuracy and Task Completion we will explain how to determine whether a Microsoft Foundry agent is genuinely ready for business use, rather than simply impressive in a demonstration.<\/p>\n\n\n\n<!--more-->\n\n\n\n<p class=\"wp-block-paragraph\">The problem is that an agent can produce a confident, well-written response while still using unsupported information, calling the wrong business system or leaving the requested task unfinished. Unless these behaviours are measured separately, leaders can approve an agent that looks accurate but creates more work and risk.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">What Microsoft Foundry agent evaluation actually measures<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Microsoft Foundry provides a managed environment for building, testing and monitoring AI applications and agents. An agent combines an AI model with instructions, approved business information and tools that let it perform actions such as searching SharePoint, checking an order or creating a service ticket.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Foundry evaluators work like repeatable quality tests. They run realistic requests through the agent and score different parts of its behaviour, including whether its answer is supported, whether it selected the right tools and whether it completed the overall task.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This builds on the design controls covered in our guide to building Microsoft Foundry agents with Microsoft Agent Framework. Evaluation provides the evidence needed to decide whether those controls work under realistic conditions.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Why one accuracy score is not enough<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">There is no single score that proves an agent is reliable. A useful evaluation program should examine at least three separate questions.<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Groundedness:<\/strong> Is the answer supported by the information supplied to the agent?<\/li>\n<li><strong>Tool call accuracy:<\/strong> Did the agent select the correct business tool and provide the right information to it?<\/li>\n<li><strong>Task completion:<\/strong> Did the user receive the complete and usable outcome they requested?<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">These measures expose different failures. An answer may be grounded in an HR policy but fail to check the employee\u2019s actual leave balance. An agent may call the correct finance tool but use the wrong customer number. It might complete a task while ignoring an approval requirement.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Groundedness tests whether answers have evidence<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Groundedness measures whether claims in an agent\u2019s response are supported by the context it was given. That context might come from a policy document, a customer record, an Azure AI Search result or another approved source.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Importantly, groundedness is not the same as general factual accuracy. If an answer happens to be correct but the supplied source does not support it, the response should still be treated as ungrounded. The agent has effectively guessed.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">For example, imagine an employee asks whether unused annual leave can be carried into the next year. The agent retrieves the company leave policy but adds a limit that does not appear anywhere in that document. Most of the answer may sound reasonable, but the unsupported limit is still a business risk.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">We explain the underlying retrieval approach in more detail in Boost Accuracy with Azure AI Groundedness. During evaluation, the focus shifts from designing grounded responses to proving that they remain grounded across hundreds of realistic questions.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">A simple groundedness check<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">The Azure AI Evaluation software development kit provides a groundedness evaluator. It uses a separate AI model as a judge to compare the response with its supporting context and return a score.<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>import os\nfrom azure.ai.evaluation import GroundednessEvaluator\n\nmodel_config = {\n &quot;azure_endpoint&quot;: os.environ[&quot;AZURE_OPENAI_ENDPOINT&quot;],\n &quot;api_key&quot;: os.environ[&quot;AZURE_OPENAI_KEY&quot;],\n &quot;azure_deployment&quot;: os.environ[&quot;AZURE_OPENAI_DEPLOYMENT&quot;]\n}\n\nevaluator = GroundednessEvaluator(\n model_config=model_config,\n threshold=4\n)\n\nresult = evaluator(\n query=&quot;Can unused annual leave be carried forward?&quot;,\n context=&quot;Unused annual leave remains available unless employment ends.&quot;,\n response=&quot;Yes. Unused annual leave remains available for future use.&quot;\n)\n\nprint(result)<\/code><\/pre>\n\n\n\n<p class=\"wp-block-paragraph\">The threshold should reflect the consequences of an incorrect answer. A general internal knowledge assistant may tolerate occasional low-risk failures. An agent dealing with financial approvals, legal obligations or customer commitments requires a much stricter release standard.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Tool call accuracy tests the agent\u2019s decisions<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Tools are the controlled connections an agent uses to perform work. They might retrieve a Microsoft 365 document, query a customer system, create an IT ticket or request approval from a manager.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Tool call accuracy checks whether the agent chose the correct tool and supplied suitable details. This matters because a polished final response can hide a poor or unsafe process.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Consider an agent asked to disable access for an employee leaving on Friday. It may correctly understand the request but schedule the action for the wrong date, target the wrong account or bypass the required manager approval. Evaluating only the final message would miss these failures.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Your test data should therefore record the expected tool, important input values and whether approval is required. Foundry can then compare the agent\u2019s activity with the expected process.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Task completion measures the business outcome<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Task completion asks the most practical question: did the agent finish the job and produce something the user can use?<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">If a user requests a summary of three incidents, their current status and recommended next actions, returning an accurate summary of only two incidents is not successful. The response may be grounded and well written, but the requested deliverable is incomplete.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Microsoft Foundry\u2019s Task Completion evaluator examines the conversation and returns a pass or fail result based on whether the user\u2019s requirements were met. This is particularly useful for multi-step activities such as onboarding, service desk triage and document preparation.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Some agent evaluators, including Task Completion, remain preview capabilities. They should be validated against human review before being used as the only basis for a high-risk production decision.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Build tests around real work rather than ideal prompts<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">A useful evaluation set should reflect how employees and customers actually communicate. Include incomplete questions, spelling mistakes, conflicting instructions, missing records, unavailable tools and requests from users without the necessary permission.<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li><strong>Start with common tasks.<\/strong> Use requests that represent the bulk of the agent\u2019s expected workload.<\/li>\n<li><strong>Add edge cases.<\/strong> Test missing information, ambiguous names, duplicate records and system outages.<\/li>\n<li><strong>Include permission tests.<\/strong> Confirm that users cannot retrieve or update information outside their role.<\/li>\n<li><strong>Define the expected outcome.<\/strong> Record the correct source, tool, approval path and final deliverable.<\/li>\n<li><strong>Review failed and passed examples.<\/strong> A pass rate is useful, but individual results explain what must change.<\/li>\n<\/ol>\n\n\n\n<p class=\"wp-block-paragraph\">Evaluation should also be complemented by deliberate security testing. Our article on why Microsoft Foundry agents need red teaming explains how to test data leakage, manipulated instructions and attempts to bypass approvals.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">What the combined results can reveal<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Consider an illustrative 180-person professional services firm testing an internal HR agent. Initial results showed 93 per cent groundedness, which appeared strong, but task completion was only 74 per cent.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The agent usually quoted the correct policies. However, it regularly failed to call the leave-balance tool or explain the next approval step. Employees still needed HR to finish the request manually, limiting the expected productivity gain.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">After separating the measures, the team improved its tool instructions, added missing test cases and made approval requirements explicit. The business could then assess the agent based on reduced HR workload, not simply the quality of its writing.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Set release gates leaders can understand<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">A practical scorecard might require a minimum groundedness pass rate, zero unauthorised tool actions and a task completion target for priority workflows. High-risk failures should block release even when the overall average appears acceptable.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">These controls also support Australian governance expectations. They do not deliver Essential 8 compliance on their own, but they complement the Australian government\u2019s cybersecurity framework by encouraging controlled access, strong authentication, logging and clear approval boundaries.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Testing should continue after launch. Business documents change, tools are updated and user behaviour rarely matches the original test plan. Regular sampling of production interactions helps detect declining accuracy before it becomes an operational problem.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Move from an impressive agent to a dependable one<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Groundedness tells you whether the answer has evidence. Tool call accuracy tells you whether the agent used business systems correctly. Task completion tells you whether useful work was actually finished.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Together, these measures give CIOs and CTOs a far more credible basis for investment and release decisions. They help prevent incorrect answers, unsafe actions and AI projects that quietly shift work back to employees.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">CloudProInc combines more than 20 years of enterprise IT experience with practical expertise across Microsoft Foundry, Azure, OpenAI, Claude and cybersecurity. As a Melbourne-based Microsoft Partner and Wiz Security Integrator, we help organisations test agents against real business outcomes rather than demonstration results.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">If you are not sure whether your Foundry agent is ready for employees or customers, we are happy to review the evaluation approach and identify the gaps before they become expensive problems.<\/p>\n\n\n","protected":false},"excerpt":{"rendered":"<p>Learn how to test whether Microsoft Foundry agents use approved information, call the right tools and finish business tasks before small AI errors become costly failures.<\/p>\n","protected":false},"author":1,"featured_media":58360,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_yoast_wpseo_opengraph-title":"Task Completion: Evaluate Groundedness and Tool Accuracy","_yoast_wpseo_opengraph-description":"Task completion evaluation reveals whether AI agents use supported 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