veto_local_llm

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

Annotations already indicate non-read-only (readOnlyHint=false) and non-destructive (destructiveHint=false). The description adds the behavioral trait of avoiding cloud providers, but does not detail potential side effects, latency, or error handling beyond that. It provides moderate added context beyond annotations.

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 extremely concise: two sentences with no superfluous words. The first sentence states the function, and the second provides usage guidance. Every sentence earns its place.

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?

Given the tool has 4 parameters (1 required), full schema coverage, no output schema, and the description covers purpose and usage, it is fairly complete. The agent_response parameter is explained in the schema, and the description lacks only deeper behavioral details (e.g., response structure), but overall it provides enough context for proper invocation.

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?

All four parameters are fully described in the input schema (100% coverage). The description does not add new meaning beyond what the schema provides; it mentions 'Ollama or LM Studio' which aligns with the provider enum. No additional semantic value is added.

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 clearly states the tool's purpose: routing a task to a local LLM (via Ollama or LM Studio) instead of a cloud provider. The verb 'routes' and specific resource ('task to local LLM') make it highly specific, and it distinguishes itself from sibling tools like 'veto_route_task' by emphasizing local execution.

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 explicit guidance on when to use the tool: for 'privacy-sensitive data or simple, repetitive tasks.' This implies suitable scenarios and hints at alternatives (cloud LLMs), though it does not explicitly list when not to use or detailed exclusions.

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