Low Risk

describe_tool_input

Get the input schema for one or more tools. It is a good idea to call this tool first to understand how to successfully call execute_tool.

Part of the Cloudinary Asset Management server.

describe_tool_input is read-only, but an agent in a loop can still rack up calls and cost. PolicyLayer caps every call before it runs. Live in minutes.

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AI agents call describe_tool_input to retrieve information from Cloudinary Asset Management without modifying any data. This is common in research, monitoring, and reporting workflows where the agent needs context before taking action. Because read operations don't change state, they are generally safe to allow without restrictions -- but you may still want rate limits to control API costs.

Even though describe_tool_input only reads data, uncontrolled read access can leak sensitive information or rack up API costs. An agent caught in a retry loop could make thousands of calls per minute. A rate limit gives you a safety net without blocking legitimate use.

Read-only tools are safe to allow by default. No rate limit needed unless you want to control costs.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "describe_tool_input": {}
  }
}

See the full Cloudinary Asset Management policy for all 26 tools.

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

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View all 26 tools →

These attack patterns abuse exactly the kind of access describe_tool_input 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 describe_tool_input only ever does what you allow.

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Other read tools across the catalogue. The same approach applies to each: allow, with a rate cap to control cost.

What does the describe_tool_input tool do? +

Get the input schema for one or more tools. It is a good idea to call this tool first to understand how to successfully call execute_tool.. It is categorised as a Read tool in the Cloudinary Asset Management MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on describe_tool_input? +

Register the Cloudinary Asset Management MCP server in PolicyLayer and add a rule for describe_tool_input: 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 Cloudinary Asset Management. Nothing to install.

What risk level is describe_tool_input? +

describe_tool_input is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit describe_tool_input? +

Yes. Add a rate_limit block to the describe_tool_input 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 describe_tool_input completely? +

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

describe_tool_input is provided by the Cloudinary Asset Management MCP server (cloudinary/asset-management-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Cloudinary Asset Management tool call.

Deterministic rules across all 26 Cloudinary Asset Management tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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4,600+ MCP servers and 31,000+ tools scanned and risk-classified.

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