Retrieve the full, untruncated proctor exam result stored by a prior run_exam_for_mirror call. run_exam_for_mirror returns a truncated summary to keep the response within MCP size limits. This tool provides on-demand access to the complete result data, including full tool input schemas and detail...
AI agents call get_exam_result to retrieve information from Pointsyeah without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves and queries exam result data that was previously stored by another function (run_exam_for_mirror). It has no side effects, does not modify data, execute code, delete anything, or involve financial operations. The filtering capability confirms it is a read-only query mechanism.
From the tool's definition Tool name contains 'get_exam_result' and description states 'Retrieve the full, untruncated proctor exam result' and 'provides on-demand access to the complete result data'.
Risk signalsBulk/mass operation — affects multiple targets
Attacks that exploit this kind of access
Retrieve the full, untruncated proctor exam result stored by a prior run_exam_for_mirror call. run_exam_for_mirror returns a truncated summary to keep the response within MCP size limits. This tool provides on-demand access to the complete result data, including full tool input schemas and detailed exam output. Supports filtering by section (exam_results, logs, summary, errors) and by mirror_id to drill into specific parts of the result without loading the entire payload. Tip: For servers with many tools, the full result can be very large. Use the section and/or mirror_id filters to retrieve only the data you need. Typical usage: 1. Call run_exam_for_mirror — note the returned result_id 2. Call get_exam_result with that result_id and a section filter (e.g., section=. It is categorised as a Read tool in the Pointsyeah MCP Server, which means it retrieves data without modifying state.
Register the Pointsyeah MCP server in PolicyLayer and add a rule for get_exam_result: 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 Pointsyeah. Nothing to install.
get_exam_result 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 get_exam_result 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 get_exam_result. 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.
get_exam_result is provided by the Pointsyeah MCP server (slack-workspace-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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