Medium Risk

add_comment

Post a new comment on any target in a workspace: a row, a cell, a doc text range, an html element, an entire surface, or the workspace itself. Polymorphic target shape mirrors the REST POST /api/workspaces/:slug/comments. For threading, pass parentId to hang the new comment as a reply (the server...

Risk signalsAccepts raw HTML/template content (body) · Bulk/mass operation — affects multiple targets

Part of the Dock server.

add_comment can modify Dock 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_comment to create or modify resources in Dock. 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_comment 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 Dock.

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

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

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

Post a new comment on any target in a workspace: a row, a cell, a doc text range, an html element, an entire surface, or the workspace itself. Polymorphic target shape mirrors the REST POST /api/workspaces/:slug/comments. For threading, pass parentId to hang the new comment as a reply (the server flattens nested replies to single depth and auto-unresolves a resolved parent). Mentions are an array of { kind: 'user'|'agent', id, label } triples; the server validates each mention's access to the workspace before accepting. Fires comment.added (and comment.unresolved when a reply reopens a resolved parent). For replies to existing comments where you don't want to reconstruct the target, prefer reply_to_comment which derives the target from the parent. Editor or commenter role required.. It is categorised as a Write tool in the Dock 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_comment? +

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

What risk level is add_comment? +

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

Can I rate-limit add_comment? +

Yes. Add a rate_limit block to the add_comment 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_comment completely? +

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

add_comment is provided by the Dock MCP server (https://trydock.ai/api/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Dock tool call.

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