get_preferences

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

With no annotations the description carries the full burden, and it does well: it discloses the auth requirement ('Requires login') and the conditional behavior that `project_id` causes (returns the project layer plus the effective merge). It omits any note on side effects or rate limits, but for a read/lookup tool the disclosure is solid.

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?

Front-loaded on the core purpose, then details the return shape. Dense jargon ('facet layer', 'effective merge') is domain-specific rather than filler, though the catalog enumeration makes it longer than strictly necessary.

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?

No output schema and no annotations, so the description has to describe the return payload itself, and it does: the `user`/`project`/`effective` layers plus the `catalog` fields (scope, kind, label, default kano/weight/threshold, constraint flag). That is enough to call and interpret the tool, with only minor ambiguity about the catalog's exact shape.

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 coverage is 0%, so the description must compensate, and it does: it explains that `project_id` triggers inclusion of the `project` layer on top of the always-returned `user` layer. It does not state the ID format, but the semantic effect of the parameter is clear.

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+resource ('Show the caller's STANDING facet layer') and explains exactly what layer is returned and how it relates to the `recommend` tool. It implicitly contrasts with `set_preferences` (read vs. set) but never names that sibling explicitly, so differentiation is inferred rather than stated.

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?

Usage is implied by the resource description and the 'Requires login' prerequisite, but there is no explicit when-to-use, when-not-to-use, or pointer to `set_preferences` for mutation. An agent can infer the read use case but must reason about the alternative itself.

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