draft_email_reply
Structure an email thread for reply drafting. Parses the thread, extracts context (from, subject, date), and builds a reply prompt with your instructions and desired tone. Returns a structured draft ready to review and send via send_email, or to refine via call_llm.
This record as markdown: /tools/io-github-homenshum-nodebench/draft-email-reply.md
What draft_email_reply does on Nodebench
AI agents use draft_email_reply 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 draft_email_reply is rated Medium
This tool creates and structures new email content (draft composition), which is a reversible write operation. While it does not directly send emails (that is delegated to send_email), it generates email body content that modifies communication.
From the tool's definition Tool description states it 'builds a reply prompt' and returns 'a structured draft ready to review and send via send_email'. The draft_email_reply function creates new email content (write operation) that is intended to be sent.
Attacks that exploit this kind of access
The rule that runs draft_email_reply 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 draft_email_reply, this is the rule to start with:
draft_email_reply 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 draft_email_reply call is checked against it from then on.
Questions about draft_email_reply
Structure an email thread for reply drafting. Parses the thread, extracts context (from, subject, date), and builds a reply prompt with your instructions and desired tone. Returns a structured draft ready to review and send via send_email, or to refine via call_llm. 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 draft_email_reply: 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.
draft_email_reply 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 draft_email_reply 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 draft_email_reply. 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.
draft_email_reply 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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