Medium Risk

agents_prompt_history

List past versions of an agent's prompt_text. Every edit to the agent's prompt is snapshotted to an append-only table — use this tool to browse history, find a prior known-good version, and copy it into agents.prompt_restore.

Risk signalsBulk/mass operation — affects multiple targets

Part of the Dialogbrain server.

agents_prompt_history can modify Dialogbrain 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 agents_prompt_history to create or modify resources in Dialogbrain. 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 agents_prompt_history 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 Dialogbrain.

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

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

See the full Dialogbrain policy for all 157 tools.

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

Browse the full MCP Attack Database →

Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so agents_prompt_history 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 agents_prompt_history tool do? +

List past versions of an agent's prompt_text. Every edit to the agent's prompt is snapshotted to an append-only table — use this tool to browse history, find a prior known-good version, and copy it into agents.prompt_restore.. It is categorised as a Write tool in the Dialogbrain MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on agents_prompt_history? +

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

What risk level is agents_prompt_history? +

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

Can I rate-limit agents_prompt_history? +

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

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

agents_prompt_history is provided by the Dialogbrain MCP server (https://api.dialogbrain.com/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Dialogbrain tool call.

Deterministic rules across all 157 Dialogbrain tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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