local_ask

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

With no annotations provided, the description carries the full burden and does so thoroughly. It discloses the token-budget behavior of the think parameter, warns that a tight max_tokens can cause an empty answer, and notes that thinking is only available for models with that capability. This is valuable operational context beyond the schema.

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 front-loaded with the core purpose, followed by concise usage guidance and a well-structured Args list. Every sentence adds meaningful information; there is no filler or redundancy. The length is justified by the number of parameters and the critical think-related warning.

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 is complete for a 7-parameter tool with no annotations. It explains the return type, all parameters, usage boundaries, and a non-obvious behavioral trap. Combined with the presence of an output schema, nothing essential is missing for an agent to select and invoke the tool correctly.

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 description coverage is 0%, and the description fully compensates by explaining every parameter: model references list_models, prompt is the actual instruction, system is role/behavior, temperature is determinism vs creativity, max_tokens is a cap, context is prepended text, and think explains the reasoning trace with its trade-off. This is exemplary parameter documentation.

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?

States a specific verb and resource: 'Asks a local model a question and returns the answer as text.' It also distinguishes itself from the sibling local_structured by explicitly saying to use that tool for machine-processable results. The purpose is clear, specific, and differentiated.

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?

Explicitly gives usage context: 'For free-text tasks: writing, rewriting, summarizing, explaining.' It also states the alternative: 'If a machine-processable result is needed, use local_structured instead.' This gives the agent clear when-to-use and when-not-to-use guidance.

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