Ask the local AI

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

The description helpfully discloses privacy behavior (data stays local) and no-mutation behavior ('does not change anything') which aligns with readOnlyHint=true. However, it also says it 'may read the web,' which is an interaction with external entities and contradicts the openWorldHint=false annotation. This inconsistency undermines the behavioral contract.

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?

Three short sentences, front-loaded with the core action and then the privacy/behavioral traits. Nearly every sentence earns its place; only the web-reading clause introduces ambiguity rather than value.

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?

With no output schema, the description should signal what comes back; it does so loosely ('the question and answer stay on the user's computers'), and annotations cover the safety profile. It is largely complete for a two-parameter read tool, with the only gap being the unresolved web-access behavior.

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 100%, so both the 'model' and 'prompt' parameters are already documented, including the reference to list_local_models. The description adds no parameter meaning beyond the schema, so baseline 3 applies.

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 ('Ask an AI model running on the user's own computer, through Toskar'), which is clear and concrete. It doesn't explicitly distinguish itself from search_my_knowledge, though it hints at the boundary by noting it 'may read the web or the user's connected knowledge.' The purpose is clear but sibling differentiation is left implicit.

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 implies a use case (asking a local AI a question) and gestures at the knowledge-search overlap, but never states when to use this versus search_my_knowledge or list_local_models. Usage is implied rather than directed.

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