setup_validate
Validate a kernel config (20+ checks: JSON structure, device connectivity, adapter compatibility). Returns validation errors and warnings.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| config | Yes | Kernel config JSON to validate |
Validate a kernel config (20+ checks: JSON structure, device connectivity, adapter compatibility). Returns validation errors and warnings.
| Name | Required | Description | Default |
|---|---|---|---|
| config | Yes | Kernel config JSON to validate |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=false and destructiveHint=false, so safety is covered, and the description adds that the call returns errors and warnings plus the breadth of checks (20+). Notably it does not explain why a validation tool is flagged non-read-only (e.g., live device connectivity probing), leaving a small behavioral ambiguity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two tight sentences with the action and check scope front-loaded. Nothing is wasted, though it is thin rather than deliberately minimal.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a nested-object input with no output schema, the description helpfully states the return shape (errors and warnings), which compensates for the missing output schema. It still omits any linkage to how the config is produced or what a passing result means before registration, so an agent must infer the workflow position.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for the single nested config parameter, so the schema already carries the semantics; the description adds no format or shape detail beyond calling it a 'kernel config JSON'. Baseline 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Names a specific verb (Validate) and resource (kernel config) and enumerates the check categories covered (JSON structure, device connectivity, adapter compatibility). It does not, however, distinguish itself from setup_detect, setup_test_job, or setup_status, which sit in the same setup_* family.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no statement of when to call this versus siblings such as setup_generate_config, setup_test_job, or setup_register_device. Usage is only inferable from the tool name, which is the bare minimum an agent could guess without a description at all.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.