Medium Risk

bulk_mark_complete

Bulk mark multiple stories as complete in a single API call. Each story entry needs a story_id, summary, and review_type. Uses the ORCH key.

Part of the Loopctl server.

bulk_mark_complete can modify Loopctl 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 bulk_mark_complete to create or modify resources in Loopctl. 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 bulk_mark_complete 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 Loopctl.

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

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

See the full Loopctl policy for all 52 tools.

Get this rule live on your own Loopctl server in minutes. PolicyLayer enforces it on every call, before it runs.

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

Bulk mark multiple stories as complete in a single API call. Each story entry needs a story_id, summary, and review_type. Uses the ORCH key.. It is categorised as a Write tool in the Loopctl MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on bulk_mark_complete? +

Register the Loopctl MCP server in PolicyLayer and add a rule for bulk_mark_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 Loopctl. Nothing to install.

What risk level is bulk_mark_complete? +

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

Can I rate-limit bulk_mark_complete? +

Yes. Add a rate_limit block to the bulk_mark_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 bulk_mark_complete completely? +

Set action: deny in the PolicyLayer policy for bulk_mark_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 bulk_mark_complete? +

bulk_mark_complete is provided by the Loopctl MCP server (loopctl-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Loopctl tool call.

Deterministic rules across all 52 Loopctl tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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