save_dm_automation

SERVERHermoso SOURCEhttps://app.hermoso.ai/mcp

Medium RISK CLASS

Category Write

Parameters 00 required

Recommended Rate-limitedsee the rule below

Registry record Grade D, identity unverified Pull the record →

This record as markdown: /tools/hermoso/save-dm-automation.md

WHAT IT DOES

What save_dm_automation does on Hermoso

AI agents use save_dm_automation to create or update resources in Hermoso, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Hermoso environment.

RISK

Why save_dm_automation is rated Medium

An AI agent can call save_dm_automation faster than any human can review: one bad instruction and it creates or modifies resources in Hermoso by the hundred, each call as confident as the last.

Risk signalsBulk/mass operation — affects multiple targets

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs save_dm_automation safely

PolicyLayer is an MCP gateway: it sits between your AI agents and Hermoso, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For save_dm_automation, this is the rule to start with:

save_dm_automation Rate-limited

save_dm_automation 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.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "save_dm_automation": {
      "limits": [
        {
          "counter": "save_dm_automation_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

LIMIT THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect Hermoso, apply this rule, and every save_dm_automation call is checked against it from then on.

FAQ

Questions about save_dm_automation

What does the save_dm_automation tool do? +

Create (no id) or edit (id) a ManyChat-style automation. Instagram/Facebook: a keyword comment (one post, the next post, any post; on Facebook also ads) gets a private reply in DMs/Messenger, a DM keyword or ig.me/m.me ref link gets a message, with optional link buttons and rotated public replies. X: a keyword @mention or a reply under your post gets a public reply, a DM keyword gets a DM (X allows an automated DM only after the person DMed you). Once per person per post; a DM saying STOP opts that person out. Instagram and Facebook are free; X is billed in credits for every mention, reply or DM X delivers to the account plus each reply or DM sent, and running out stops the X rules. It messages real people, so confirm the text first. It is categorised as a Write tool in the Hermoso MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on save_dm_automation? +

Register the Hermoso MCP server in PolicyLayer and add a rule for save_dm_automation: 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 Hermoso. Nothing to install.

What risk level is save_dm_automation? +

save_dm_automation is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit save_dm_automation? +

Yes. Add a rate_limit block to the save_dm_automation 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.

How do I block save_dm_automation completely? +

Set action: deny in the PolicyLayer policy for save_dm_automation. 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.

What MCP server provides save_dm_automation? +

save_dm_automation is provided by the Hermoso MCP server (https://app.hermoso.ai/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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