Add a dependency between two tasks. The task will depend on the specified task (must be completed first). Args: task_id: ID of the task that will have the dependency depends_on_id: ID of the task it depends on Returns: Confirmation with updated task info
AI agents use add_dependency to create or update resources in Taskdog — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Taskdog environment.
Adding a dependency creates a new relationship between tasks and modifies task state (dependencies), making it a Write operation. It's reversible (a dependency can presumably be removed), so it's not Destructive. The severity is medium because incorrect dependencies could impact task scheduling and workflow optimization, but the effect is limited to task metadata relationships, not data deletion or financial impact.
From the tool's definition The tool modifies task relationships by adding a dependency between two tasks. The description states it updates task info and establishes a dependency relationship, which is a reversible structural change to task metadata.
Documented attack patterns abuse exactly the kind of access add_dependency gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Taskdog, and nothing reaches the server without passing your rules. This is the rule we recommend for add_dependency:
{
"version": "1",
"default": "deny",
"tools": {
"add_dependency": {
"limits": [
{
"counter": "add_dependency_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}add_dependency 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.
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Add a dependency between two tasks. The task will depend on the specified task (must be completed first). Args: task_id: ID of the task that will have the dependency depends_on_id: ID of the task it depends on Returns: Confirmation with updated task info. It is categorised as a Write tool in the Taskdog MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Taskdog MCP server in PolicyLayer and add a rule for add_dependency: 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 Taskdog. Nothing to install.
add_dependency is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the add_dependency 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 add_dependency. 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.
add_dependency is provided by the Taskdog MCP server (kohei-wada/taskdog). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Taskdog, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
Free to start. No card required.
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