get_job_details_resource

Get detailed information for a specific job.

Server PyTorch HUD MCP Server izaitsevfb/claude-pytorch-treehugger
Category Read
Risk class Low
Parameters 00 required

What get_job_details_resource does on PyTorch HUD MCP Server

AI agents call get_job_details_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.

Why get_job_details_resource needs a policy

This tool retrieves and queries job details from PyTorch CI/CD analytics without creating, modifying, deleting, or executing operations. It has no side effects beyond data retrieval. The low severity reflects minimal blast radius—accessing CI/CD job information poses no direct risk to systems, data integrity, or financial assets.

From the tool's definition Tool name 'get_job_details_resource' and description 'Get detailed information for a specific job' indicate a retrieval operation with no modification capability.

Questions about get_job_details_resource

What does the get_job_details_resource tool do? +

Get detailed information for a specific job. It is categorised as a Read tool in the PyTorch HUD MCP Server MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on get_job_details_resource? +

Register the PyTorch HUD MCP Server MCP server in PolicyLayer and add a rule for get_job_details_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.

What risk level is get_job_details_resource? +

get_job_details_resource is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit get_job_details_resource? +

Yes. Add a rate_limit block to the get_job_details_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.

How do I block get_job_details_resource completely? +

Set action: deny in the PolicyLayer policy for get_job_details_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.

What MCP server provides get_job_details_resource? +

get_job_details_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.

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