robot_mirror

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

Without annotations, the description carries the behavioral burden. It explains that the tool downloads ontologies and generates a catalog file, but does not disclose side effects (e.g., file overwriting), required permissions, or performance implications. More detail on the caching process would improve transparency.

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 two succinct sentences with clear front-loading of purpose. Every word contributes to understanding the core function without 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?

Despite having a clear purpose, the description omits crucial details for correct usage: behaviors of boolean flags like 'strict' and 'xml_entities', meaning of 'prefixes' and 'add_prefix', and effects of 'extra_args'. With 12 parameters and no annotations, completeness is inadequate.

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?

With 0% schema description coverage, the description must explain parameters. It only clarifies 'directory' and 'output' implicitly, but leaves 10 other parameters (e.g., prefixes, add_prefix, strict, extra_args) undocumented, failing to compensate for the schema gap.

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 the tool 'mirrors (caches) external ontology imports locally', specifies actions (downloads to directory, generates catalog XML), and distinguishes it from siblings like robot_convert or robot_extract by focusing on offline caching of imports.

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?

The description implies usage when network reliability is a concern ('prevents network failures from breaking builds'), but does not explicitly state when to use this tool versus alternatives, nor does it provide exclusions or prerequisites.

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