switch_backend

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions that backend_id comes 'from settings.json' and returns a 'confirmation message with current status', which adds some context. However, it lacks critical details: whether this requires specific permissions, if it's a destructive change affecting ongoing processes, rate limits, or error conditions. For a mutation tool with zero annotation coverage, this is insufficient.

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 well-structured and concise. It front-loads the purpose in the first sentence, followed by clear 'Args' and 'Returns' sections. Every sentence earns its place by providing essential information without redundancy or fluff.

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's complexity (a mutation with one parameter) and the presence of an output schema (which handles return values), the description is minimally complete. It covers the purpose and parameter semantics but lacks behavioral context and usage guidelines. With no annotations, it should do more to explain permissions, side effects, or error handling for a backend-switching operation.

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 description coverage is 0%, so the description must compensate. It adds meaningful semantics: 'backend_id' is described as 'ID of the backend to switch to (from settings.json)', clarifying the source and purpose beyond the bare schema. Since there's only one parameter, this adequately covers its semantics, though it doesn't specify format or constraints.

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: 'Switch the active LLM backend.' This is a specific verb ('switch') with a clear resource ('active LLM backend'). However, it doesn't explicitly differentiate from its sibling 'switch_model' (which might switch models within a backend), leaving some ambiguity about sibling distinction.

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 no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing to know backend IDs from settings.json), exclusions, or compare it to sibling tools like 'switch_model' or 'models'. The agent must infer usage context solely from the purpose statement.

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