query_ollama

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

With no annotations, the description provides one behavioral trait: automatic injection of agent personality as system context. However, it does not disclose other traits like rate limits, auth needs, or side effects. Adequate but minimal for a simple query tool.

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?

Two concise sentences that front-load the core purpose and a key behavioral detail. No wasted words; every sentence is valuable.

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 simple tool with two parameters and an output schema, the description covers the main functionality and a behavioral note. Slightly lacking in guidance and transparency, but complete enough given the tool's simplicity and schema richness.

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 the baseline is 3. The description adds no extra meaning beyond the schema for the 'prompt' and 'model' parameters, neither clarifying input formats nor listing available models.

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 sends a prompt to a local Ollama instance for inference, using a specific verb and resource. It distinguishes itself from sibling tools by specifying 'local Ollama' and mentioning automatic personality injection.

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 usage for local model inference with system context, but no explicit guidance on when to use this tool versus alternatives (e.g., other AI tools). It lacks when-not-to-use or alternative references.

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