classifier_robustness

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

Discloses that the tool returns evaluation results and is informational (no side effects implied). However, lacks details on output format, permissions, or any potential limitations. Without annotations, this is acceptable but not thorough.

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?

Two concise sentences: first defines the tool, second gives usage guidance. No wasted words, efficient and front-loaded.

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?

Provides sufficient context for a parameterless tool: what it returns and why to use it. Could benefit from describing output format, but overall complete for its purpose.

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?

No parameters defined, so description adds necessary context by explaining the nature of the results (performance under perturbed/OOD inputs). Schema coverage is 100% (empty), and the description compensates for lack of param details.

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?

Clearly states it provides adversarial-robustness results for the live censorship classifier. Distinguishes from siblings like classifier_score (which gives a score) by specifying performance under perturbed/OOD inputs.

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 advises using the tool to understand failure modes before relying on a classifier score. Provides clear context but does not explicitly list when not to use it or name alternative tools.

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