AI agents call flaky_test_detector to retrieve information from Testrail without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves and analyzes historical test result data to detect flaky tests. It has no side effects, does not modify or delete data, does not execute external operations, and does not involve financial transactions. The flagging of flakiness is a read-only analytical operation that identifies patterns in existing data.
From the tool's definition Tool description states 'Pull this case's result across the last N runs' - the verb 'pull' indicates data retrieval without modification.
Attacks that exploit this kind of access
Pull this case's result across the last N runs and flag flakiness. It is categorised as a Read tool in the Testrail MCP Server, which means it retrieves data without modifying state.
Register the Testrail MCP server in PolicyLayer and add a rule for flaky_test_detector: 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 Testrail. Nothing to install.
flaky_test_detector 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 flaky_test_detector 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 flaky_test_detector. 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.
flaky_test_detector is provided by the Testrail MCP server (sergey-bl/testrail-mcp). 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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