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conduyt_sms_delivery_report

Get SMS provider delivery outcomes for automation drips: entered vs delivered, rejected, provider-error, dead-end counts, plus rejection reasons. See what the provider did with your SMS sends.

Instructions

SMS provider delivery-outcome report for external-workflow SMS drips: per-automation entered vs delivered / rejected (invalid, litigator, DNC) / provider-error / workflow dead-end, plus a send-attempt 'why rejected' reason breakdown (line_type = 'not mobile' often WRONGLY rejected; landline_skipped / no_phone_skipped = Conduyt's own recorded skips). Use to answer 'what did the SMS provider do with our drips?'

Input Schema

NameRequiredDescriptionDefault
toNoISO end
fromNoISO start (omit both for the last 180 days; spans clamp to 180d)
smartListIdNoScope to contacts in this smart list
automationIdNoScope to one automation

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv4.71.0

TDQS

A3.9/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does real work: it flags that line_type = 'not mobile' is often wrongly rejected and that landline_skipped / no_phone_skipped are Conduyt's own recorded skips rather than provider outcomes — exactly the kind of interpretive caveat that prevents misreading data. It does not say anything about read-only nature, freshness, or result size, which is the remaining gap.

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?

Purpose and metric inventory are front-loaded in the first clause, and the closing use-case sentence is short and purposeful. The nested parentheticals make it dense and slightly hard to scan, but no sentence is filler.

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 annotations and no output schema, the description substitutes by describing the report's contents and the semantic traps in the data, which is the main thing an agent needs to interpret results. Scoping behavior for automationId/smartListId is the only meaningful omission.

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 description coverage is 100%, including the useful note that omitting from/to defaults to the last 180 days and clamps spans. The description adds no parameter-level detail of its own beyond the word "per-automation", so baseline 3 applies.

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 names a specific resource (SMS provider delivery-outcome report) and enumerates exactly what it breaks down: entered vs delivered / rejected / provider-error / workflow dead-end, plus a rejection-reason breakdown. That is far more precise than a tautology, though it never names the adjacent `conduyt_sms_drip_conversion_report` sibling it is most likely to be confused with.

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?

"Use to answer 'what did the SMS provider do with our drips?'" gives a clear selection context and implicitly separates it from a conversion/funnel-style report. It stops short of explicit exclusions or naming alternatives when the agent should pick something else.

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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