tool_describe
Returns everything needed to call a tool correctly: its complete JSON Schema, every parameter with type and default, and examples known to work. Pair it with tool.search — search to find the name, describe to learn the shape, then call. This exists so the catalogue does not have to be loaded into...
This record as markdown: /tools/com-fluentedi-tools/tool-describe.md
What tool_describe does on Tools
AI agents call tool_describe to retrieve information from Tools without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
name | string | Yes | Tool name, e.g. "time.window". Underscores and slashes are accepted too. |
Parameters from the server's own tool schema.
Why tool_describe is rated Low
Even though tool_describe only reads data, uncontrolled read access leaks sensitive information and racks up API costs: an agent caught in a retry loop can make thousands of calls a minute without anyone noticing.
Risk signalsBulk/mass operation — affects multiple targets
Attacks that exploit this kind of access
The rule that runs tool_describe safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Tools, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For tool_describe, this is the rule to start with:
tool_describe is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Tools, apply this rule, and every tool_describe call is checked against it from then on.
Questions about tool_describe
Returns everything needed to call a tool correctly: its complete JSON Schema, every parameter with type and default, and examples known to work. Pair it with tool.search — search to find the name, describe to learn the shape, then call. This exists so the catalogue does not have to be loaded into context up front. It is categorised as a Read tool in the Tools MCP Server, which means it retrieves data without modifying state.
tool_describe accepts 1 parameter: name. Required: name. The full parameter table on this page comes from the server's own tool schema.
Register the Tools MCP server in PolicyLayer and add a rule for tool_describe: 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 Tools. Nothing to install.
tool_describe is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the tool_describe 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 tool_describe. 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.
tool_describe is provided by the Tools MCP server (https://fluentedi.com/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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