get_tenant_default_preference

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

The description states the tool is a read operation ('Read a tenant's...'), but annotations include destructiveHint=true, which contradicts the read-only nature. This is a serious inconsistency, lowering the transparency score.

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 concise, well-structured with clear sections (purpose, when/not to use, returns), and contains 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?

For a read operation with good annotations, the description is mostly complete. It states the return type (full default-preference tree) but lacks detail on the structure, which would be helpful given no output schema.

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 baseline is 3. The description does not add meaningful detail beyond what the schema already provides for tenant_id and workspace.

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 reads a tenant's default category preferences, which are the inheritance baseline for new users. It explicitly distinguishes from sibling tools for individual user/object preferences.

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 provides when-to-use scenarios (before update, for diagnosing) and when-not-to-use with alternative tools (get_suprsend_user_preferences, get_suprsend_object_preferences).

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