ask_local_model

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

With no annotations, the description carries full burden. It discloses key limitations: delegated models cannot read/edit files, only return text, and the main agent handles validation/edits/tests. However, it does not mention other behaviors like authentication or rate limits, though those may be less relevant for a local model.

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 sentences, efficiently front-loading the core action and return value in the first sentence and adding behavioral context in the second. No unnecessary words.

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?

Despite the output schema existing, the description lacks guidance on parameter usage (e.g., prompt format, model selection, temperature tuning). It covers behavioral context but is incomplete for a tool with 6 parameters, leaving the agent to infer usage from parameter names alone.

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 coverage is 0% (no descriptions in schema) and the description does not explain any of the 6 parameters (prompt, model, system, etc.). It adds no meaning beyond the schema's type/name information, failing to compensate for the lack of param descriptions.

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 action ('Send a prompt to a backend model') and its output ('return text plus metadata'). It also distinguishes from sibling tools (which are configuration/list tools) by focusing on actual model interaction.

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 explains that delegated models cannot read/edit files, and the main agent retains responsibility for validation/edits/tests. This provides context on when to use this tool (offloading reasoning) but does not explicitly state when not to use or name alternatives.

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