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by io.github.SautiKit
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start_dialer_campaign

Idempotent

SPENDS MONEY: start dialing a draft campaign; each call bills telco (and AMD tokens) from the wallet up to the campaign budget. NEVER call this without explicit human confirmation naming the campaign, its contact count and its budget.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "campaign_id": "<campaign_id>"
    },
    "name": "start_dialer_campaign"
  }
}

Input Schema

NameRequiredDescriptionDefault
purposeNoRequired on tools that read data or reports; recommended on every tool. One sentence: what you are doing and why (for example "finding this caller's open ticket to answer them"). Building a report, dashboard, analytics or an export is a SautiDesk Pro feature done by the report tools, not by pulling records.
campaign_idYescampaign UUID

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior5/5

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

Annotations only declare idempotency and non-destructiveness; the description adds the crucial economic behavior the annotations omit — per-call telco and AMD token billing drawn from the wallet, capped at the campaign budget. This is exactly the kind of cost/authorization context annotations cannot express.

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?

Two dense sentences: the warning and cost model first, the guardrail second. No filler, and the highest-risk information is front-loaded in capitals.

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 money-spending, irreversible-in-practice action the description covers cost source, budget ceiling and the required confirmation. It stops short of saying what happens to in-flight calls or how to stop it (pause_dialer_campaign), a minor gap given annotations already signal idempotency.

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

Parameters3/5

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

Schema coverage is 100%, so campaign_id and purpose are already documented in the schema. The description mentions campaign, contact count and budget as human-confirmation data, which helps framing but does not map to a parameter (contact count and budget are not inputs). Baseline 3 applies.

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 ("start dialing a draft campaign") and immediately disambiguates scope by noting it is a draft campaign, which separates it from resume/pause siblings. The leading "SPENDS MONEY" tag makes the operation's nature unmistakable at a glance.

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 an explicit precondition and a hard prohibition: never call without explicit human confirmation naming the campaign, contact count and budget. It does not name the alternative for a paused (rather than draft) campaign, e.g. resume_dialer_campaign, so routing between the two remains partly inferential.

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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