e164_checkValidate a phone number's E.164 structure (+CC, 8-15 digits, no leading zero).
| Name | Required | Description | Default |
|---|---|---|---|
| phone | Yes | International phone number, e.g. +14155552671. |
| Name | Required | Description | Default |
|---|---|---|---|
| tool | No | ||
| scope | No | ||
| valid | Yes | ||
| reason | Yes | ||
| country | No | ||
| normalized | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark the operation read-only and idempotent. The description adds the behavioral validation rules (country code, total digit count, no leading zero), which an agent needs to understand what this check actually tests.
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?
One tightly scoped sentence that front-loads the main action and packs the essential validation criteria. No filler or redundant restating of the tool name.
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 single-parameter validation tool with an output schema and safety annotations, the description covers what the tool does, what it checks, and its exact format requirements. Nothing needed for correct invocation is missing.
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% (the phone parameter is described with an example), but the description goes beyond the schema by defining the exact E.164 constraints: +CC, 8-15 digits, no leading zero. This adds semantic meaning not present in the schema's bare 'International phone number' phrasing.
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 uses a specific verb ('Validate') and a precise resource ('a phone number's E.164 structure'), and spells out the format rules (+CC, 8-15 digits, no leading zero). This makes it easy to distinguish from sibling validators like iban_check or isbn_check.
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 gives clear context: use this tool when you need to validate an international phone number against E.164 formatting. It doesn't explicitly name exclusions or alternative tools, but the format-specific scope is unambiguous among the sibling validators.
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 distinct identifier type or data source: every checksum validation is for a specific standard (IBAN, LEI, VAT, etc.), and the on-chain and rental tools are clearly separate domains. There is no ambiguity between tools; even similar-sounding checks like 'luhn_check' and 'ean13_check' are distinct algorithms with explicit descriptions.
Most validation tools follow a 'X_check' pattern (iban_check, swift_bic_check, ein_format_check), but others deviate: 'company_number_format' uses a noun_noun structure, 'block_info' is noun_noun, and 'batch_validate' and 'context_distill' use verbs. While the pattern is not uniform, the names are readable and the convention is understandable, just not fully consistent.
With 28 tools, this server exceeds the typical 3-15 well-scoped range and even the 16-25 heavy range. The server covers multiple unrelated domains (identifier validation, blockchain queries, rental fraud, text processing), which inflates the count. While each tool is individually justified, the overall surface feels overly broad for a single MCP server.
For each sub-domain, coverage is strong: identifier validation includes a wide range of international standards, on-chain queries cover balances, activity, and settlement history, and rental tools provide risk, verdict, and deposit guard. Minor gaps exist (e.g., no country-specific tax IDs beyond what's listed, no transaction history for arbitrary tokens), but the visible coverage is comprehensive for the stated purposes.