generate_zero_draft
Auto-draft an artifact (slack message, email, spec doc, PR draft, architecture note, career plan, or content brief) based on detected signals and causal chains. Returns draft for human approval before sending.
This record as markdown: /tools/io-github-homenshum-nodebench/generate-zero-draft.md
What generate_zero_draft does on Nodebench
AI agents use generate_zero_draft 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 generate_zero_draft is rated Medium
This tool generates new content (drafts) that will be written/sent to external systems (Slack, email) or stored as documents. While the description notes that drafts require 'human approval before sending,' the tool itself performs the Write action of creating content artifacts. It does not execute code, delete data, or move money.
From the tool's definition Tool description states it 'Auto-draft an artifact (slack message, email, spec doc, PR draft, architecture note, career plan, or content brief)' and 'Returns draft for human approval before sending.' The key verbs are 'draft' and the artifacts created include…
Attacks that exploit this kind of access
The rule that runs generate_zero_draft 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 generate_zero_draft, this is the rule to start with:
generate_zero_draft 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 generate_zero_draft call is checked against it from then on.
Questions about generate_zero_draft
Auto-draft an artifact (slack message, email, spec doc, PR draft, architecture note, career plan, or content brief) based on detected signals and causal chains. Returns draft for human approval before sending. 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 generate_zero_draft: 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.
generate_zero_draft 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 generate_zero_draft 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 generate_zero_draft. 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.
generate_zero_draft 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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