route_regions

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

With no annotations provided, the description fully covers behavioral traits: read-only, no model calls, ignores file contents, uses file paths as metadata. This is transparent and sets correct expectations.

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?

Description is extremely concise: two clear sentences. First sentence states purpose, second lists exclusions. No wasted words; front-loaded and easy to parse.

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?

Tool has 6 parameters, no output schema, and no annotations. The description only addresses file metadata, omitting details on other parameters and return behavior. Incomplete for reliable agent use.

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 only briefly mentions 'files' as weak metadata. It does not explain the purpose or expected values for goal, context, problem, top_k, or min_score, leaving agents without essential guidance.

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?

Description clearly states the tool recommends Brain Regions using local deterministic rules, distinguishing it from siblings like list_regions. It specifies what the tool does not do (call models, read memory, etc.), leaving no ambiguity.

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?

Description explicitly states the tool is read-only and lists what it does not do (call models, read memory, trigger other tools), guiding appropriate use. However, it lacks explicit comparison to sibling tools or when to prefer alternatives.

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