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find_contact

Resolve a contact's user namespace from a phone number or channel user ID. Returns all matches if ambiguous, leaving user_ns unset instead of guessing.

Instructions

Resolve a user_ns from a phone number or a channel user_id.

Pass exactly one of phone (Ecuador +593 normalization applied) or user_id (a channel-native id such as a WhatsApp wa_id). Read-only. If several contacts match a phone it returns them all and leaves user_ns None rather than guessing.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
phoneNo
user_idNo
Install Server

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations available, the description carries the full burden and does well: it labels the operation read-only, discloses phone normalization, and explains the ambiguous-match behavior of returning all matches while leaving `user_ns` None. It could add no-match or error behavior, but the key behavioral traits are covered.

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?

Three tightly packed sentences lead with the core purpose and immediately follow with the only usage constraint and the notable edge-case behavior. Every sentence adds value and none are redundant with the schema.

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

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple two-parameter lookup with no output schema or annotations, the description is nearly complete: it defines inputs, constraints, normalization, read-only status, and ambiguous-match handling. It stops short of specifying no-match behavior or exact response shape, but those gaps are minor here.

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

Parameters5/5

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

Schema description coverage is 0%, and the description fully compensates by explaining both parameters, their relationship (exactly one), phone normalization, and what `user_id` means with a concrete example. An agent can construct correct arguments without needing extra schema documentation.

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

Purpose4/5

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

The description clearly states a specific action ('Resolve a user_ns') and the two input keys that drive the lookup, making the tool's purpose obvious. It does not explicitly name a sibling to distinguish against, but the resolution-focused wording separates it from related contact 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 gives explicit usage guidance: pass exactly one of `phone` or `user_id`, and it even explains the Ecuadorian normalization and WhatsApp `wa_id` example. It does not discuss when to prefer this over `get_contact` or `list_contacts`, but it provides clear enough context for the intended use.

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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