Classify a PAN entity type from its 4th character (P=Person, C=Company, H=HUF, F=Firm). Stateless check: records no decision or dashboard timeline trace.
Classify a PAN entity type from the 4th character (P=Person, C=Company, H=HUF, F=Firm, ...). Stateless validator: records no decision and leaves no dashboard timeline trace.
| Name | Required | Description | Default |
|---|---|---|---|
| pan | Yes |
Changes observed during successful MCP inspections.
v0.5.4Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description fully carries the behavioral disclosure burden. It explicitly states the tool is stateless, records no decision, and leaves no dashboard timeline trace, which are meaningful behavioral traits for an agent deciding whether to invoke it. It also reveals the classification logic (4th character), enhancing 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 sentences, front-loaded with the primary action, and includes only relevant detail (classification rule and statelessness). No unnecessary words or repetition of schema fields.
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?
The tool has no output schema and no annotations, yet the description does not explain the return value or error behavior for invalid PAN inputs. While the classification rule helps, an agent cannot know what response to expect. The statelessness note is useful but does not complete the context for a tool with no structured output definition.
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 schema provides only the parameter name 'pan' and type string, with zero description coverage. The description adds that the input is a PAN and that classification depends on its 4th character, giving some semantic context. However, it does not specify the expected format, length, or validation rules for the 'pan' value, leaving a gap in parameter 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 clearly states the tool's function with a specific verb and resource: 'Classify a PAN entity type from the 4th character' and provides the mapping shorthand. This distinguishes it from sibling validators/classifiers by its unique focus on PAN entity type classification.
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 provides an implied usage context: when you need to classify a PAN entity type. It does not explicitly mention alternatives or when-not-to-use scenarios, but the statelessness note ('records no decision and leaves no dashboard timeline trace') offers some contextual guidance. However, no direct comparison to sibling tools is made.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.