Medium Risk

add_task_dependency

Add a dependency between tasks. Use this to express that a task is blocked by another task (must complete first) or relates to it. This prevents context contamination: when Task B depends on Task A, agents working on Task B will be warned if Task A is still in progress.

Part of the ContextLayer server.

add_task_dependency can modify ContextLayer 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 add_task_dependency to create or modify resources in ContextLayer. 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 add_task_dependency 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 ContextLayer.

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

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

See the full ContextLayer policy for all 62 tools.

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These attack patterns abuse exactly the kind of access add_task_dependency 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 add_task_dependency 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 add_task_dependency tool do? +

Add a dependency between tasks. Use this to express that a task is blocked by another task (must complete first) or relates to it. This prevents context contamination: when Task B depends on Task A, agents working on Task B will be warned if Task A is still in progress.. It is categorised as a Write tool in the ContextLayer MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on add_task_dependency? +

Register the ContextLayer MCP server in PolicyLayer and add a rule for add_task_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 ContextLayer. Nothing to install.

What risk level is add_task_dependency? +

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

Can I rate-limit add_task_dependency? +

Yes. Add a rate_limit block to the add_task_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.

How do I block add_task_dependency completely? +

Set action: deny in the PolicyLayer policy for add_task_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.

What MCP server provides add_task_dependency? +

add_task_dependency is provided by the ContextLayer MCP server (https://api.dotnova.io/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every ContextLayer tool call.

Deterministic rules across all 62 ContextLayer tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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