ein_format_checkValidate US Employer Identification Number FORMAT (NN-NNNNNNN). No public EIN checksum exists.
| Name | Required | Description | Default |
|---|---|---|---|
| ein | Yes | US EIN, 9 digits; dashes/spaces allowed. |
| 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 declare readOnlyHint and idempotentHint. The description adds a crucial behavioral trait: since no public checksum exists, the tool only validates format and cannot confirm a real EIN. This prevents agents from over-interpreting results and goes beyond the structured annotations.
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 short sentences with no filler. The core action and the key limitation are both front-loaded. Every word earns its place.
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 a high-coverage schema, a true output schema, and read-only/idempotent annotations, the description covers the essential behavioral caveat (no checksum). No missing information that would prevent correct invocation.
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 property description already includes '9 digits; dashes/spaces allowed.' The description's format pattern (NN-NNNNNNN) and example reinforce the hyphen placement but add little beyond what the schema already provides. Baseline 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?
States the verb 'Validate' with resource 'US Employer Identification Number FORMAT' and specifies the exact format pattern (NN-NNNNNNN). The caveat 'No public EIN checksum exists' distinguishes it from sibling checksum-based validators (e.g., luhn_check, vat_mod97_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 implies when to use it—when format validation for a US EIN is needed—but does not name alternatives or state when not to use it. The 'No checksum' note hints at a limitation but doesn't explicitly route the agent to sibling tools.
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 specific function (e.g., IBAN vs. EIN vs. block info), with no overlap even among similar validation routines. The batch and rental tools combine distinct sub-checks without ambiguity, making misselection unlikely.
Tool names are uniformly snake_case and mostly follow a descriptive pattern, but the action verbs vary (e.g., 'check', 'format', 'info', 'guard', 'verdict') rather than a single verb_noun structure. While clearly readable, the pattern is not perfectly uniform.
At 28 tools, the server feels like a broad utility pack rather than a focused domain. The count exceeds the 'heavy' threshold and includes three distinct sub-domains (financial identifiers, rental fraud, on-chain queries), making the surface area hard to navigate coherently.
The identifier validation coverage is thorough (most common checksums), rental checks cover risk, deposit, and verdict, and on-chain tools handle balances, activity, and settlement history. Minor gaps exist (e.g., no token transfer history, no generic identifier detection) but agents can likely work around them.