add_provider

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It does not mention side effects (e.g., whether an existing provider is overwritten), permission requirements, error handling, or reversibility. The only behavioral hint is the suggestion to list models after adding, which is mild context but insufficient for a mutation tool.

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 two concise sentences, front-loaded with the purpose. It includes actionable follow-up steps without unnecessary fluff. Every sentence earns its place, making it easy for an agent to parse quickly.

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?

The description covers the core action and next steps, but it lacks parameter semantics and any mention of error conditions, idempotency, or prerequisites. The presence of an output schema helps, but without annotations and with 0% schema coverage, the description remains incomplete for a tool with four required parameters.

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 schema has zero descriptions, and the description only explains the 'type' parameter with example values. The other three parameters (name, api_key, base_url) are left entirely to their names, with no added meaning. With 0% schema coverage, the description should compensate but only covers one of four parameters, leaving the rest under-specified.

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 action ('Add a new LLM provider') with a specific verb and resource. It also provides example type values (openai/deepseek/qwen/groq/custom), which helps distinguish this add operation from sibling tools like update_provider. The purpose is unambiguous and action-oriented.

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?

Provides explicit post-add guidance: call list_models to confirm availability or use add_model to manually add model names. This gives clear context on how to use the tool and what to do next. However, it does not explicitly state when not to use this tool (e.g., for updating existing providers) or name alternatives, so it loses one point.

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