Retry a failed or discarded GoodJob background job. Re-enqueues the job for processing. Use cases: - Retry a job that failed due to a transient error - Re-process a discarded job after fixing the underlying issue
AI agents invoke retry_good_job to trigger actions in Playwright Stealth. 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.
This tool triggers re-execution of a background job, which constitutes running an external operation. The effects depend on what the re-enqueued job does, which is unknown and could range from benign to significant. It does not simply read data, nor does it irreversibly delete anything — it re-queues a job for processing, making Execute the most appropriate category.
From the tool's definition Retry a failed or discarded GoodJob background job. Re-enqueues the job for processing.
Documented attack patterns abuse exactly the kind of access retry_good_job gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Playwright Stealth, and nothing reaches the server without passing your rules. This is the rule we recommend for retry_good_job:
{
"version": "1",
"default": "deny",
"tools": {
"retry_good_job": {
"limits": [
{
"counter": "retry_good_job_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}retry_good_job 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.
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Retry a failed or discarded GoodJob background job. Re-enqueues the job for processing. Use cases: - Retry a job that failed due to a transient error - Re-process a discarded job after fixing the underlying issue. It is categorised as a Execute tool in the Playwright Stealth MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Playwright Stealth MCP server in PolicyLayer and add a rule for retry_good_job: 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 Playwright Stealth. Nothing to install.
retry_good_job is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the retry_good_job 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 retry_good_job. 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.
retry_good_job is provided by the Playwright Stealth MCP server (pulsemcp/mcp-servers). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Playwright Stealth, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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68 Playwright Stealth tools catalogued and risk-classified — across an index of 43,000+ MCP servers.