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validate_imei

Check an IMEI's validity using the Luhn algorithm and identify its TAC (device-model code). Does not verify device status.

Instructions

USE THIS to verify a phone/device IMEI before relying on it — never assume a 15-digit string is valid or guess its check digit. Checks the Luhn check digit (and recognises the 16-digit IMEISV form), and returns the TAC (device-model code). Validates the number only — does NOT check whether the device is real, active, or blocklisted/stolen.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
imeiYesThe 15-digit IMEI (or 16-digit IMEISV); spaces and dashes are ignored.
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden. It discloses key behaviors: Luhn check digit validation, IMEISV recognition, TAC extraction, and the explicit limitation that it does not verify device existence or blocklist status. This gives the agent a clear behavioral model.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise—two sentences—with the first sentence acting as an imperative front-load. Every word adds value: usage instruction, core function, and clear limitations. No superfluous text.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

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 no output schema, the description is fully complete. It explains input format, validation algorithm, output (TAC), and limitations. The agent has all necessary context to use the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Although schema coverage is 100% (only one parameter), the description adds crucial semantics beyond the schema: it specifies the expected length (15 or 16 digits) and clarifies that spaces/dashes are ignored. This helps the agent format input correctly.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses specific verbs ('verify, check, returns') and clearly identifies the resource (IMEI). It distinguishes from sibling tools by explicitly stating what it does NOT do (check device real/active/blocklisted), setting it apart from other validation tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description begins with a strong usage directive ('USE THIS to verify...') and clarifies the tool's scope by listing exclusions (does not check device status). While it doesn't name specific alternative tools, the context of sibling validation tools makes the niche clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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