USE THIS to verify an SSCC (GS1 Serial Shipping Container Code — identifies a pallet/carton/logistics unit) from a shipping label before relying on it. Checks the 18-digit GS1 mod-10 check digit and returns the extension digit and GS1 prefix country. Validates structure only.
| Name | Required | Description | Default |
|---|---|---|---|
| sscc | Yes | The 18-digit SSCC; spaces and dashes are ignored. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, indicating no side effects. The description adds behavioral context by confirming it 'validates structure only' and detailing what it returns (extension digit, prefix country), which goes beyond the annotation.
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 a single, well-structured paragraph that fronts the action directive 'USE THIS to verify'. Every sentence is informative and concise, with no superfluous text.
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?
Without an output schema, the description adequately explains the return values (extension digit, GS1 prefix country) and clarifies that only structural validation is performed. This provides sufficient context for an agent to understand the tool's capabilities.
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 one parameter 'sscc' with a description covering format and whitespace handling (100% coverage). The description reinforces the 18-digit requirement and mentions the check digit, but adds no new semantic information beyond what the schema provides.
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 purpose: verify an SSCC code. It explains what SSCC is, what it checks (check digit, extension digit, prefix country), and that it validates structure only. This distinguishes it from sibling validation tools which are for different identifiers.
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 explicitly says 'USE THIS to verify ... before relying on it', providing clear context for when to use. However, it does not mention when not to use or explicitly compare to alternatives, though the sibling list makes the domain obvious.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a specific identifier or operation (e.g., validate_iban, parse_date, is_holiday). Even similar tools like validate_isbn and validate_isbn10 are distinct by version. There is no overlap or ambiguity.
Most tools follow a verb_noun pattern (validate_xxx, parse_xxx, format_currency). The exception is 'next_holiday', which uses an adjective instead of a verb. Otherwise consistent.
With 47 tools, the set is very large. While each tool is distinct, the count exceeds the recommended range (25+ is considered too many) and may overwhelm users or agents.
Covers a wide array of international identifiers and utilities, but notable gaps exist (e.g., no Canada SIN, India PAN, Mexico CURP). The set is broad but not exhaustive for the domain of data validation.