Format a phone number according to country conventions.
| Name | Required | Description | Default |
|---|---|---|---|
| number | Yes | Phone number to format | |
| country | No | Country code (US, UK, DE, FR, etc.) | US |
| Name | Required | Description | Default |
|---|---|---|---|
| error | No | ||
| input | Yes | ||
| country | No | ||
| formatted | No | ||
| digits_only | No | ||
| country_code | No | ||
| international | No |
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?
No annotations are provided, so the description carries full responsibility for behavioral disclosure. It only mentions 'according to country conventions' without detailing error handling, edge cases, or whether it can handle multiple formats. This is insufficient for a formatting tool that depends on country-specific rules.
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 sentence that is concise and front-loaded with the core action. However, it could benefit from a brief additional sentence about output or usage without becoming verbose.
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 complexity of phone formatting (different country conventions, input validation, output format), the description is too brief. It does not mention return value structure (though output schema exists, it's not described here). The tool could benefit from more details on accepted input formats and error behavior.
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%, and parameter descriptions are clear ('Phone number to format', 'Country code (US, UK, DE, FR, etc.)'). The description adds the context of 'country conventions' but does not explain the default country behavior or accepted codes beyond what the schema provides. Baseline score of 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 formats a phone number according to country conventions. It specifies the verb 'Format' and the resource 'phone number'. However, it does not differentiate from sibling tools like generate_phones or validate_phone, which could cause confusion about when to use this tool over others.
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 no guidance on when or when not to use this tool. It does not mention alternatives or prerequisites. For example, it doesn't specify if the input number should already be in a particular format or if the tool handles invalid numbers.
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.
Many tools have overlapping purposes, such as multiple random generators (random_integer, random_number), duplicate hashing functions (hash_md5, md5_checksum), and near-identical tools (compare, compare_2, compare_decimals). The sheer number of tools and lack of clear boundaries make it difficult for an agent to differentiate.
Naming is highly inconsistent. There are duplicate tools with different names (camel_case vs to_camel_case, slug vs slugify), arbitrary suffixes like '_2', and mixing of patterns (e.g., generate_password vs password_entropy). No clear convention is followed.
With 572 tools, the server is massively overpopulated for any coherent purpose. It includes trivial endpoints (true_endpoint, null, hello_world) and numerous duplicates, far exceeding a well-scoped utility set.
While the server covers many domains (math, strings, dates, colors, etc.), the presence of duplicate and trivial tools indicates a lack of thoughtful curation. There are gaps in basic operations (e.g., no dedicated file or network tools), and many tools are redundant.
