Extract test results specifically from a log file.
AI agents call extract_test_results_resource to retrieve information from PyTorch HUD MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool performs a query/read operation on log data to pull out test results. It has no side effects—it does not modify logs, execute commands, delete data, or trigger external operations. The action is purely informational retrieval, making it a Read category tool with low severity since misuse would only expose CI/CD analytics data rather than cause system changes or data loss.
From the tool's definition Tool name 'extract_test_results_resource' and description 'Extract test results specifically from a log file' indicate data retrieval and analysis.
Attacks that exploit this kind of access
Extract test results specifically from a log file. It is categorised as a Read tool in the PyTorch HUD MCP Server MCP Server, which means it retrieves data without modifying state.
Register the PyTorch HUD MCP Server MCP server in PolicyLayer and add a rule for extract_test_results_resource: 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 PyTorch HUD MCP Server. Nothing to install.
extract_test_results_resource 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 extract_test_results_resource 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 extract_test_results_resource. 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.
extract_test_results_resource is provided by the PyTorch HUD MCP Server MCP server (izaitsevfb/claude-pytorch-treehugger). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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