fill_faces

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

No annotations are provided, so the description carries the full burden. It usefully discloses the 'closed edge loop' precondition and the selection semantics, but is silent on failure behavior for non-closed loops, whether the operation is destructive/undoable, and any permission needs.

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-loads the core action in one line, then qualifications, then structured Args/Returns. Every sentence earns its place with no padding.

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?

An output schema exists, so the brief 'Returns: Confirmation dict' is sufficient. Purpose, usage, and parameter meaning are covered; only edge-case/error disclosure is thin for a mutation tool with no annotations.

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%, so the description must compensate, and it largely does: it explains both parameters, spells out the enum meaning of 'ALL' vs 'CURRENT', notes the default, and points to the select_* tools for the CURRENT case. object_name is only restated ('Name of the mesh object'), which is self-evident.

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 ('Fill selected edges with a face') and adds the mechanism ('Creates faces from a closed edge loop'), so the agent knows this is a topology-creation op. It does not explicitly distinguish itself from near-siblings like bridge_edge_loops or grid_fill, which is the only gap.

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?

Gives concrete use cases ('closing gaps in meshes or capping open ends') and a prerequisite flow ('Use the select_* tools to choose first' when selection=CURRENT). No explicit when-not guidance, e.g. what to use instead for open loops, so it stops short of a 5.

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