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Set the contact channels an agent hands out

set_agent_contact_channels

Set the meeting link, email, phone, WhatsApp and Telegram that the AI agent gives out when a visitor asks how to get in touch or book a call. Omitted channels are cleared, so always send the full set you want the agent to have. Write operation, no credit cost.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesAgent id
emailNo
phoneNo
telegramNo
whatsappNo
meeting_urlNoBooking link, e.g. Calendly

TDQS

A4.6/5.0
Behavior5/5

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

With no annotations, the description carries the full behavioral burden and does so well. It explicitly warns that omitted channels are cleared, requires sending the full set, identifies the operation as a write, and notes there is no credit cost. This is non-obvious, important behavior disclosed upfront.

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 sentences, each earning its place: the purpose, the critical clearing caveat, and the write/no-cost note. The most important behavioral warning is front-loaded before the billing note.

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 setter with no annotations and no output schema, the description covers purpose, parameters, destructive behavior, and cost. It does not describe the response or error behavior, but that is a minor gap for this straightforward write operation.

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 only 33%, but the description compensates by explaining that the parameters represent the channels the agent gives out and that all desired channels must be sent together. It adds the critical clear-on-omit semantics. Individual field formats are not detailed, but the names are self-explanatory.

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 names a specific operation (set contact channels), the exact resource (an AI agent's hand-out contact info), and the fields involved (meeting link, email, phone, WhatsApp, Telegram). It is clearly differentiated from sibling tools like set_agent_avatar, set_agent_company, and set_agent_voice.

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 clear context for when to use the tool: when a visitor asks how to get in touch or book a call. It does not explicitly name alternatives or exclusion cases, but the context is specific enough that an agent can recognize when this tool applies.

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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TDQS

B3.1/5.0
Disambiguation2/5

Despite consistently detailed descriptions, several tool pairs have unclear boundaries: `get_subscription_limits` and `get_agent_plan_limits` describe essentially the same agent-slot check, `crm_get_conversation` and `crm_communication_thread` both claim to return the full message thread, and `get_credit_usage_by_agent` vs `get_credit_usage_for_agent` differ only by preposition. At 149 tools, an agent will regularly misselect between these near-duplicates.

Naming Consistency4/5

The dominant pattern is verb_noun with domain prefixes (`crm_*`, `sdr_*`) and a consistent `preview_*` family that maps cleanly to destructive/expensive actions. Deviations are minor but real: CRM deletes use the inverted `delete_crm_*` form while other CRM ops use `crm_*`, and credit-usage tools mix `by_agent`/`for_agent` prepositions.

Tool Count1/5

149 tools is nearly three times the 50+ threshold the rubric treats as extreme, even though the platform genuinely spans agents, campaigns, audiences, CRM, SDR, billing, and connections. Many could be consolidated without losing capability — e.g. the 11 balance/credit-usage tools, the two LinkedIn-account listers, and the 15+ preview variants.

Completeness5/5

The surface is remarkably complete: full CRUD/lifecycle coverage for agents, campaigns, audiences, CRM leads/stages, and SDR searches, plus billing, analytics, and connection management. Destructive or costly operations all have preview/approval counterparts, so there are no dead ends. If anything the risk is over-coverage rather than gaps.

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