data-processor

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. However, it reveals nothing about the tool's behavior—whether it's read-only or destructive, what permissions are needed, rate limits, side effects, or output format. This leaves the agent completely in the dark about how the tool operates.

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?

While concise with only three words, the description is under-specified rather than efficiently informative. It wastes its limited space on a tautology ('DataProcessor tool description') that adds no value, failing to front-load useful information. Conciseness should not come at the cost of clarity.

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 lack of annotations and output schema, the description is severely incomplete. It does not explain what the tool does, when to use it, behavioral traits, or return values. For a tool with one parameter, this minimal description leaves critical gaps that hinder an AI agent's ability to invoke it correctly.

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?

The input schema has 100% description coverage, with the single parameter 'message' documented as 'Message to process'. The description adds no additional meaning beyond this, such as examples, constraints, or processing context. Since the schema does the heavy lifting, the baseline score of 3 is appropriate, but the description fails to compensate or enhance understanding.

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 'DataProcessor tool description' is a tautology that merely restates the tool name with minimal variation. It provides no information about what specific action the tool performs (e.g., what type of processing), what resource it operates on, or how it differs from sibling tools like 'api-client' or 'file-handler'. This fails to help an AI agent understand when to select this 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?

The description offers no guidance on when to use this tool versus alternatives. It does not mention any context, prerequisites, exclusions, or comparisons to sibling tools. An AI agent would have no basis for choosing 'data-processor' over 'api-client' or 'file-handler' based on this description alone.

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