publish_to_queue
Push content to the LinkedIn content queue on the Convex platform. Content goes through the engagement gate and LLM judge before being scheduled for posting.
This record as markdown: /tools/io-github-homenshum-nodebench/publish-to-queue.md
What publish_to_queue does on Nodebench
AI agents use publish_to_queue to create or update resources in Nodebench, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Nodebench environment.
Why publish_to_queue is rated Medium
This tool writes content to a queue system with the intent to publish it to LinkedIn. While the content undergoes review gates before actual posting, the tool itself performs an irreversible write action that commits content to a publishing pipeline. The high severity reflects potential brand/reputation damage if malicious or incorrect content is queued without proper oversight.
From the tool's definition Tool description states 'Push content to the LinkedIn content queue' and 'scheduled for posting' — this creates/modifies data (queued content) and triggers downstream publishing actions.
Attacks that exploit this kind of access
The rule that runs publish_to_queue safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Nodebench, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For publish_to_queue, this is the rule to start with:
publish_to_queue 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.
The button opens the PolicyLayer dashboard: create your workspace, connect Nodebench, apply this rule, and every publish_to_queue call is checked against it from then on.
Questions about publish_to_queue
Push content to the LinkedIn content queue on the Convex platform. Content goes through the engagement gate and LLM judge before being scheduled for posting. It is categorised as a Write tool in the Nodebench MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Nodebench MCP server in PolicyLayer and add a rule for publish_to_queue: 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 Nodebench. Nothing to install.
publish_to_queue 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 publish_to_queue 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 publish_to_queue. 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.
publish_to_queue is provided by the Nodebench MCP server (nodebench-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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