Format evaluation results into a readable report with metrics and Studio URL. Parameters: - evaluation_result: The evaluation result dictionary from run_text_eval or agent_query_and_evaluate Returns a formatted report with metrics and Azure AI Studio URL if available
AI agents call format_evaluation_report to retrieve information from Azure AI Agent Service MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This is a data presentation utility that transforms already-computed evaluation results into a human-readable format. It retrieves/accesses existing evaluation data and reformats it for display purposes. No side effects, modifications, deletions, or external operations occur. This falls squarely into the Read category as a low-severity tool.
From the tool's definition The tool 'format_evaluation_report' takes evaluation results and formats them into a readable report with metrics and URLs.
Documented attack patterns abuse exactly the kind of access format_evaluation_report gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Azure AI Agent Service MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for format_evaluation_report:
{
"version": "1",
"default": "deny",
"tools": {
"format_evaluation_report": {}
}
}format_evaluation_report is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Format evaluation results into a readable report with metrics and Studio URL. Parameters: - evaluation_result: The evaluation result dictionary from run_text_eval or agent_query_and_evaluate Returns a formatted report with metrics and Azure AI Studio URL if available. It is categorised as a Read tool in the Azure AI Agent Service MCP Server MCP Server, which means it retrieves data without modifying state.
Register the Azure AI Agent Service MCP Server MCP server in PolicyLayer and add a rule for format_evaluation_report: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Azure AI Agent Service MCP Server. Nothing to install.
format_evaluation_report is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the format_evaluation_report rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for format_evaluation_report. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
format_evaluation_report is provided by the Azure AI Agent Service MCP Server MCP server (microsoft-foundry/mcp-foundry). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Azure AI Agent Service MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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28 Azure AI Agent Service MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.