Force trigger a GoodJob cron schedule immediately. Enqueues a new job for the specified cron schedule regardless of its normal schedule. Use cases: - Manually trigger a cron job for testing - Force an immediate run of a periodic job - Re-run a cron job that was missed
AI agents invoke force_trigger_good_job_cron to trigger actions in Langfuse Observability. 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 forcibly executes a scheduled job outside its normal schedule. It triggers external operations (background jobs) whose effects depend on which cron job is targeted — some cron jobs could have significant side effects such as data processing, notifications, or system changes.
From the tool's definition Force trigger a GoodJob cron schedule immediately. Enqueues a new job for the specified cron schedule regardless of its normal schedule.
Attacks that exploit this kind of access
Force trigger a GoodJob cron schedule immediately. Enqueues a new job for the specified cron schedule regardless of its normal schedule. Use cases: - Manually trigger a cron job for testing - Force an immediate run of a periodic job - Re-run a cron job that was missed. It is categorised as a Execute tool in the Langfuse Observability MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Langfuse Observability MCP server in PolicyLayer and add a rule for force_trigger_good_job_cron: 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 Langfuse Observability. Nothing to install.
force_trigger_good_job_cron 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 force_trigger_good_job_cron 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 force_trigger_good_job_cron. 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.
force_trigger_good_job_cron is provided by the Langfuse Observability MCP server (langfuse-observability-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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