local_complete

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

With no annotations, the description carries the burden. It discloses the core behavior (one-shot, no tools, returns text) and notes it's 'cheap' (low cost), but omits potential failure modes, authorization requirements, or network behavior (despite an endpoint parameter). It adds some value but not full transparency.

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 3 succinct sentences, front-loading the primary action and immediately differentiating from siblings. Every sentence contributes: purpose, use cases, and return value. No filler or redundancy.

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 tool with 6 parameters and sibling tools for registering models/endpoints, the description doesn't mention prerequisites or how to choose a model. It assumes the agent knows it can just pass prompt and rely on defaults, but lacks guidance on when to specify model/endpoint. Given the output schema exists, return format is covered, but operational context is incomplete.

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 parameter description coverage is 0%, and the tool description offers no parameter-specific explanation. It doesn't clarify how 'model', 'endpoint', or 'system' interact, nor does it mention defaults or dependencies. The parameter names are self-explanatory, but the description adds no semantic value beyond the schema.

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 performs one-shot completion on a local model, explicitly contrasting with agent loops and tools. It lists concrete use cases (summaries, drafts, classification, translation) and specifies the output, leaving no ambiguity about what the tool does.

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?

It explicitly identifies when to use it ('cheap offload' for simple tasks) and when not to ('no tools, no agent loop'), implicitly routing to sibling tools like run_agent for agentic needs. While it doesn't name the alternative directly, the exclusion is clear enough for an agent to decide.

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