rupa_lod

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

Annotations already indicate destructiveHint=true and readOnlyHint=false, so the description adds value by explaining that reduction always 'succeeds' but the real criterion is error tolerance. It also clarifies that the error is measured as distance to original surface, which is a useful behavioral detail.

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, front-loads the core functionality, and provides a meaningful heuristic (2% diagonal) without fluff. It's a single paragraph with no redundancy.

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?

Given the tool's moderate complexity (3 params, no output schema), the description covers the essential purpose and quality trade-off. It doesn't explain return values, but that's mitigable since no output schema exists and the description implies error metrics are provided. Slightly more detail on result format could help, but it's adequate.

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 100%, so the schema already documents all parameters. The description doesn't add much per-parameter detail, but it does frame the 'nisbah' parameter as the fraction of triangles to keep, which matches the schema description. The mention of 'same as Decimate modifier' adds context beyond the schema, but not crucial.

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 it creates a chain of LODs with geometric error measurements, and explains the trade-off between mesh reduction and quality loss. It distinguishes itself from sibling tools like rupa_rantai, but doesn't explicitly name a sibling tool.

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?

It implies usage for mesh simplification with a quality threshold ('above 2% diagonal'), but doesn't explicitly state when to use this versus alternative simplification tools (e.g., rupa_proksi) or when not to use it. It provides a general guideline but not explicit routing.

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