USE THIS to verify a SEDOL (LSE securities identifier) before relying on it. Checks the no-vowels alphabet and the weighted mod-10 check digit.
| Name | Required | Description | Default |
|---|---|---|---|
| sedol | Yes | The 7-character SEDOL, e.g. B0YBKJ7. |
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 declare readOnlyHint=true, so the description does not need to state safety. The description adds context about the validation algorithm (no-vowels, check digit), but it does not specify the return value or error behavior, which is a gap given no output schema.
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, front-loaded with a clear usage instruction. Every word adds value with no redundancy or fluff.
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?
For a simple one-parameter read-only tool, the description covers purpose and usage. However, it lacks specification of the return format (e.g., boolean or error), which is needed since there is no output schema. This reduces completeness for an agent.
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 parameter 'sedol' is fully described in the schema (100% coverage) with an example. The description adds context about SEDOL being an LSE identifier, but it does not add significant new meaning beyond what the schema already 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 verifies a SEDOL (LSE securities identifier) and specifies the validation criteria (no-vowels alphabet and weighted mod-10 check digit). It distinguishes the tool from siblings by naming the specific identifier type and the validation checks.
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 instruction 'USE THIS to verify a SEDOL before relying on it' is explicit about when to use the tool. However, it does not mention when not to use it or any alternatives among sibling validation tools, which are all different identifier types.
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.