get_system_resources

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

With no annotations, the description carries the burden and does well: it discloses the failure-mode return value ({unavailable: true} for remote/openai providers) and the meaning of the ollama_gpu field including how it is derived (env pinning vs runner process device fds). It doesn't discuss cost/latency, but for an informational read tool this is solid disclosure.

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?

Three front-loaded sentences with no filler; purpose, constraint, and usage all arrive early. The final sentence on ollama_gpu is slightly technical but its detail is load-bearing for interpreting the result.

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?

With no output schema and no annotations, the description covers the key return values ({unavailable: true}, ollama_gpu) and the provider-scoped behavior, which is most of what an agent needs. Minor gaps remain around the provider parameter's accepted values and whether other fields are returned.

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?

The single provider parameter has 0% schema description coverage, so the description must compensate. It adds useful domain context by distinguishing local ollama vs remote/openai provider behavior, but never enumerates accepted provider values or states whether the param is required/defaulted.

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?

States a specific verb+resource: reports host RAM, GPU VRAM, and currently-loaded models. The scope is distinct from model-listing siblings like list_models or get_server_info, though no sibling is named to explicitly route the agent away from them.

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?

Gives explicit when-to-use ('Use before picking a model or num_ctx for heavy jobs') and an explicit when-not ('Only works for LOCAL ollama providers — returns {unavailable: true} for remote/openai-type providers'). The agent knows both the trigger and the failure condition.

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