debug_testcase · Testdino MCP: Risk & Policy

WHAT IT DOES

What debug_testcase does on Testdino

AI agents invoke debug_testcase to trigger actions in Testdino. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.

WHY IT NEEDS A POLICY

Why debug_testcase needs a policy

debug_testcase triggers real processes with real consequences. An agent gone sideways doesn't fire it once — it starts dozens of builds, sends mass notifications, or burns through compute before anyone looks up.

Risk signalsAdmin/system-level operation

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

debug_testcase Rate-limited

debug_testcase stays usable, but rate-capped — a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "debug_testcase": {
      "limits": [
        {
          "counter": "debug_testcase_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

RATE-LIMIT THIS TOOL →

Instant setup, no code required.

PolicyLayer is an MCP gateway: every tool call is checked against your rule before it reaches Testdino, so you can run agents against it safely.

FAQ

Questions about debug_testcase

What does the debug_testcase tool do? +

Fetch historical execution and failure data for a specific test case. Returns raw historical data with test run details (ID, counter, branch), test runs summary, and a debugging prompt from the API. Each execution includes its associated test run information (testRunId, testRunCounter, branch) to help correlate failures across different test runs and branches. The AI client will analyze the data to identify failure patterns, find root causes, and provide fix suggestions. Use this when you need to debug a failing test case. Example:. It is categorised as a Execute tool in the Testdino MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on debug_testcase? +

Register the Testdino MCP server in PolicyLayer and add a rule for debug_testcase: 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 Testdino. Nothing to install.

What risk level is debug_testcase? +

debug_testcase is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.

Can I rate-limit debug_testcase? +

Yes. Add a rate_limit block to the debug_testcase 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 debug_testcase completely? +

Set action: deny in the PolicyLayer policy for debug_testcase. 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 debug_testcase? +

debug_testcase is provided by the Testdino MCP server (testdino-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.