gpu_set_threshold

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

No annotations exist, so description carries full burden. It discloses the behavior (offloading models to CPU when threshold exceeded) and the range. However, it does not state side effects like whether the change is persistent, affects running models, or requires a restart. For a setting tool, this is adequate but not comprehensive.

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 sentences: first defines the action and range, second explains the consequence. No wasted words, front-loaded with key info. Ideal conciseness.

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 simple one-parameter tool with no output schema, the description covers purpose, range, and effect. It could mention persistence or validation of out-of-range values, but overall it is reasonably complete for an AI agent to use 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?

Schema description coverage is 0%, so the description must compensate. It does by providing the valid range (50-95%) and the effect, adding meaning beyond the schema's default of 82 and type integer. This is a strong compensation.

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?

Description clearly states 'Set the VRAM auto-management threshold' with a specific verb and resource. It explains the range (50-95%) and the effect (models offloaded to CPU when VRAM exceeds). This distinguishes it from sibling tools like gpu_auto_manage or gpu_flush_models.

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 usage is implied (when you want to change the threshold), but no explicit guidance is given on when to use this vs. alternatives like gpu_auto_manage (likely toggles auto-management) or gpu_optimize. No exclusions or prerequisites mentioned.

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