AI agents use record_test_result to create or update resources in Entroly Context Engine — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Entroly Context Engine environment.
The name suggests this tool records (writes) test results, likely storing them persistently. With no description available, confidence is low. Given the server context (AI coding agent, codebase analysis), this likely writes test outcome data to some store. Severity is medium as misuse could corrupt test history or metrics, but it's likely reversible.
From the tool's definition Tool name 'record_test_result' implies writing/storing test outcome data. Description is empty and uninformative.
Documented attack patterns abuse exactly the kind of access record_test_result gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Entroly Context Engine, and nothing reaches the server without passing your rules. This is the rule we recommend for record_test_result:
{
"version": "1",
"default": "deny",
"tools": {
"record_test_result": {
"limits": [
{
"counter": "record_test_result_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}record_test_result stays usable, but capped — an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.
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record_test_result. It is categorised as a Write tool in the Entroly Context Engine MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Entroly Context Engine MCP server in PolicyLayer and add a rule for record_test_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 Entroly Context Engine. Nothing to install.
record_test_result is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the record_test_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 record_test_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.
record_test_result is provided by the Entroly Context Engine MCP server (juyterman1000/entroly). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Entroly Context Engine, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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52 Entroly Context Engine tools catalogued and risk-classified — across an index of 43,000+ MCP servers.