create_classifier

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

No annotations are provided, so the description must disclose behavioral traits. The description only states creation and that classifiers can be added to collections and used in jobs. It does not mention side effects, idempotency, error handling, or what happens on duplicate names. This is insufficient for a creation tool.

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 sentences: first sentence states the core action and resource, second provides usage context. Extremely concise with no wasted words.

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 has 5 required parameters, an output schema, and no annotations, the description is brief but covers the core purpose and usage scenario. However, it lacks behavioral and lifecycle details that would help an agent use it correctly. Output schema exists but description doesn't mention it.

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% with each parameter already described in the input schema. The description adds no specific parameter details beyond what the schema provides. Baseline 3 is appropriate.

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 creates a custom data classifier for specific patterns, and distinguishes from built-in classifiers by mentioning when to use (when built-in don't cover data types). It also mentions that custom classifiers can be added to collections and used in jobs, which adds context.

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 says 'Use when ALTR's built-in classifiers don't cover your data types,' providing clear when-to-use guidance. However, it does not specify when not to use or mention alternatives beyond built-in classifiers.

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