Send a message to an AI agent and get its response. The agent runs with its configured prompt, tools, and knowledge. Use this to test agents or have them process a task. Returns: {status: 'replied'|'silent', response_text, messages[], full_reply, model_used, tokens_*, send_mode, execution_mode}. ...
Part of the Dialogbrain server.
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AI agents call agents_ask to retrieve information from Dialogbrain without modifying any data. This is common in research, monitoring, and reporting workflows where the agent needs context before taking action. Because read operations don't change state, they are generally safe to allow without restrictions -- but you may still want rate limits to control API costs.
Even though agents_ask only reads data, uncontrolled read access can leak sensitive information or rack up API costs. An agent caught in a retry loop could make thousands of calls per minute. A rate limit gives you a safety net without blocking legitimate use.
Read-only tools are safe to allow by default. No rate limit needed unless you want to control costs.
{
"version": "1",
"default": "deny",
"tools": {
"agents_ask": {}
}
}See the full Dialogbrain policy for all 157 tools.
These attack patterns abuse exactly the kind of access agents_ask gives an agent. Each links to the full case and the policy that stops it:
Other read tools across the catalogue. The same approach applies to each: allow, with a rate cap to control cost.
Send a message to an AI agent and get its response. The agent runs with its configured prompt, tools, and knowledge. Use this to test agents or have them process a task. Returns: {status: 'replied'|'silent', response_text, messages[], full_reply, model_used, tokens_*, send_mode, execution_mode}. messages[] carries each messages.send invocation the agent made (text, subject, reply_to_message_id, timestamp, message_id, attachments=[{file_id,name,mime}]). full_reply concatenates text only — attachment-only sends show up in messages but not full_reply. status='silent' iff both response_text is empty AND messages is empty. Execution may take 10-60s depending on agent complexity.. It is categorised as a Read tool in the Dialogbrain MCP Server, which means it retrieves data without modifying state.
Register the Dialogbrain MCP server in PolicyLayer and add a rule for agents_ask: 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.
agents_ask is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the agents_ask 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 agents_ask. 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.
agents_ask 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.
Deterministic rules across all 157 Dialogbrain tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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