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kernel_tool_describe

Fetch a tool's full input/output schema by exact name after searching, so you load only the schemas you will call. Returns metadata matching tools/list for that single tool.

Instructions

Fetch the full input/output schema for a tool by name. Use after kernel_tool_search to load only the schemas you'll actually call. Returns the same shape that tools/list would emit for this single tool — minus the host function: this is purely metadata.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "name": "<name>"
    },
    "name": "kernel_tool_describe"
  }
}

Input Schema

NameRequiredDescriptionDefault
nameYesExact tool name as returned by kernel_tool_search.

Output Schema

NameRequiredDescriptionDefault
nameYes
tagsYes
descriptionYes
inputSchemaNo
outputSchemaNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.5.1

TDQS

A4.4/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the burden and does so well: 'purely metadata' and 'the same shape that `tools/list` would emit' tell the agent this is a side-effect-free read with a predictable payload. It doesn't address failure behavior for an unknown name, which is the main remaining gap.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three short sentences, front-loaded with the action, then the workflow, then the return characteristics. Nothing is redundant or padded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return values need no explanation, and the description still gives a useful one-line characterization of the payload. Complete for a simple metadata lookup, though it omits what happens when the name doesn't resolve.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Only one parameter at 100% schema coverage, so the schema already documents it fully. The description reinforces that the name must be one returned by kernel_tool_search, adding a small amount of provenance guidance but nothing about format or casing beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Fetch the full input/output schema for a tool by name') and explicitly positions itself relative to sibling kernel_tool_search, so an agent can distinguish it without opening the schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

'Use after `kernel_tool_search` to load only the schemas you'll actually call' gives an explicit ordering and a rationale for the two-step pattern. It stops short of saying when to skip this call (i.e., when search output already suffices), but the workflow context is clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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