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DripRaven WhatsApp campaigns

import_contacts

Bulk import contacts from a CSV string. Required columns: "phone", "name". Any additional columns become custom fields. Optional tag is applied to all imported contacts. If the tag matches an enabled automation (list_automations), each NEWLY created contact is queued for that automation's message; existing contacts are not. Returns { total, created, updated, failed, errors, automations_queued }.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagNoTag applied to every imported contact
sourceNo
csv_dataYesRaw CSV including header row

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior5/5

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

Annotations only declare it is a non-idempotent write; the description adds the material side effect that newly created contacts are queued for a matching automation while existing contacts are not, and reports the exact return counters. This is exactly the extra behavioral context annotations cannot carry.

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

Conciseness4/5

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

Front-loaded with the core action, followed by input requirements then the automation side effect; every sentence carries information. Slightly dense, and the inline return-field list could be trimmed, but nothing is wasted.

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?

With no output schema, the description usefully enumerates the return shape and documents the automation side effect, covering the mutation's consequences. The only gap is the undocumented 'source' parameter, which leaves one input ambiguous for a bulk-write tool.

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?

Schema coverage is 67%; the description compensates by explaining csv_data format (header row, required phone/name columns, extra columns as custom fields) and the tag's effect of applying to every imported contact and triggering automations. The 'source' parameter remains unexplained in both schema and description, costing a point.

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?

States a specific verb and resource ("Bulk import contacts from a CSV string") plus the scope that separates it from add_or_update_contact: bulk/CSV rather than single-contact. An agent can distinguish it from all siblings without opening the schema.

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?

Gives concrete usage conditions: required phone/name columns, extra columns become custom fields, optional tag applied to all. It also clarifies that only newly created contacts trigger automations. It never names an alternative tool or an explicit when-not (e.g. versus add_or_update_contact for single contacts), so it stops short of a 5.

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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