agents_task_complete

Report that a Claude Code agent task has been completed. Call this when you finish processing an agent_task from DialogBrain.

SERVERDialogbrain SOURCEhttps://api.dialogbrain.com/mcp

Medium RISK CLASS

Category Write

Parameters 32 required

Recommended Rate-limitedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/io-github-saloprj-dialogbrain/agents-task-complete.md

WHAT IT DOES

What agents_task_complete does on Dialogbrain

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

Parameter	Type	Required	Description
`success`	boolean	Yes	Whether the task completed successfully
`summary`	string	—	Brief summary of what was done
`trace_id`	string	Yes	Trace ID from the agent task event

Parameters from the server's own tool schema.

RISK

Why agents_task_complete is rated Medium

This tool creates or modifies data reversibly by updating task status. It does not retrieve data (Read), execute arbitrary code (Execute), permanently delete data (Destructive), or involve financial transactions (Financial).

From the tool's definition Tool name includes 'complete' and description states 'Report that a Claude Code agent task has been completed,' indicating it modifies task state by marking it as finished. This is a state change operation on existing data (the task record).

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs agents_task_complete safely

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

agents_task_complete Rate-limited

agents_task_complete 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": {
    "agents_task_complete": {
      "limits": [
        {
          "counter": "agents_task_complete_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 Dialogbrain, apply this rule, and every agents_task_complete call is checked against it from then on.

FAQ

Questions about agents_task_complete

What does the agents_task_complete tool do? +

Report that a Claude Code agent task has been completed. Call this when you finish processing an agent_task from DialogBrain. 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.

What parameters does agents_task_complete accept? +

agents_task_complete accepts 3 parameters: success, summary, trace_id. Required: success, trace_id. The full parameter table on this page comes from the server's own tool schema.

How do I enforce a policy on agents_task_complete? +

Register the Dialogbrain MCP server in PolicyLayer and add a rule for agents_task_complete: 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_task_complete? +

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

Can I rate-limit agents_task_complete? +

Yes. Add a rate_limit block to the agents_task_complete 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_task_complete completely? +

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

agents_task_complete 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.

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