Check Local Model Health

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

The description aligns with readOnlyHint=true by describing a check rather than a mutation, and it adds useful behavioral context by saying it returns availability status and model metadata. This is transparent for a read-only health-check tool with no side effects to disclose.

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?

The description is three short sentences with no filler. The core purpose comes first, the return summary second, and the usage guidance third. Every sentence adds distinct value.

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 zero-parameter read-only health check that already has an output schema, the description covers purpose, returned information, and when to invoke it. There is no missing detail an agent would need to call it correctly.

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?

There are zero parameters, and the schema coverage is 100%, so the description has no parameter documentation burden. The no-parameter baseline of 4 applies because there is nothing missing or ambiguous to explain.

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?

The description names the exact verb and resource: 'Check if the local llama.cpp server is reachable and loaded.' It also states the return value ('availability status and model metadata'), which makes the tool's purpose unmistakable and distinguishes it from the sibling implementation tools.

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?

The description provides clear trigger conditions: call before a batch of implementation tasks, or after a previous tool call fails with a connection error. It also explains the decision being made ('whether to retry or fall back to direct cloud-model implementation'). It does not explicitly state when not to use it, so it falls just short of a 5.

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