Medium Risk

send_chaser

Call this when the user wants to send a follow-up reminder or chaser email to someone about an overdue or upcoming action. The AI client drafts the message (free). Actually SENDING the email requires a Gantta plan. If the user is on trial with credits, this will work. If trial ended, prompt them ...

Part of the Gantta server.

send_chaser can modify Gantta data, with no limits today. PolicyLayer puts allow, deny, and rate-limit rules on every call. Live in minutes.

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AI agents use send_chaser to create or modify resources in Gantta. Write operations carry medium risk because an autonomous agent could trigger bulk unintended modifications. Rate limits prevent a single agent session from making hundreds of changes in rapid succession. Argument validation ensures the agent passes expected values.

Without a policy, an AI agent could call send_chaser repeatedly, creating or modifying resources faster than any human could review. PolicyLayer's rate limiting ensures write operations happen at a controlled pace, and argument validation catches malformed or unexpected inputs before they reach Gantta.

Write tools can modify data. A rate limit prevents runaway bulk operations from AI agents.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "send_chaser": {
      "limits": [
        {
          "counter": "send_chaser_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

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These attack patterns abuse exactly the kind of access send_chaser gives an agent. Each links to the full case and the policy that stops it:

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Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so send_chaser only ever does what you allow.

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Other write tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.

What does the send_chaser tool do? +

Call this when the user wants to send a follow-up reminder or chaser email to someone about an overdue or upcoming action. The AI client drafts the message (free). Actually SENDING the email requires a Gantta plan. If the user is on trial with credits, this will work. If trial ended, prompt them to sign up.. It is categorised as a Write tool in the Gantta MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on send_chaser? +

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

What risk level is send_chaser? +

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

Can I rate-limit send_chaser? +

Yes. Add a rate_limit block to the send_chaser 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 send_chaser completely? +

Set action: deny in the PolicyLayer policy for send_chaser. 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 send_chaser? +

send_chaser is provided by the Gantta MCP server (gantta/gantta-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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